Department of Electrical Engineering

The GRAPES-3 experiment is designed to perform precision studies of gamma-ray sources in the TeV-PeV energy region. It consists of 400 plastic scintillator detectors spanning an effective area of 25000 m2 and a large area (560 m2) muon telescope which records ∼ 4 x 109 muons every day. With the recent installation of an improved triggerless data acquisition (DAQ) system, the information related to every muon is recorded with a timing resolution of 10 ns. The angular resolution and pointing accuracy of the upgraded muon telescope has been validated by characterizing the shadow of the moon among recorded muons. Here, the details of the analysis and results, as well as the simulation studies to account for the deflection of the particles in the Earth’s magnetic field will be presented.

This paper presents a single-stage amplifier using substrate-integrated coaxial line (SICL) technology. It is implemented with a low-cost PCB technique at 23.35–24.05 GHz. The size of the proposed amplifier is 4.9λg×1.1λg where λg is the guided wavelength at the center frequency. In this circuit, a SICL-based bias-tee network is designed where the mounting pads are introduced for the integration of the components, such as transistor and capacitor. Next, with the help of de-embedding techniques, the input and output matching networks are designed in the SICL environment at 24 GHz. The proposed amplifier circuit exhibits 9.2 dB of peak gain with less than 1 dB of gain ripple and more than 10 dB of input/output return losses in the operating frequency band of 23.35–24.05 GHz. Moreover, the elementary blocks of the amplifier are presented in the circuit. Based on the appropriate modeling of the amplifier's elementary blocks, the simulated and measured results are in good agreement.

We report significantly enhanced sensitivity of AlGaN/GaN-based high electron mobility transistor (HEMT) sensor by the targeted synthesis of IT and 2H coexisting phase MoS2 and applying the gate bias voltage. The HEMT structures on Si (111) substrates were used for the detection of Hg2+ ions. The optimum sensitive regime in terms of V GS and V DS of the sensor was investigated by keeping the drain source voltage V DS constant at 2 V and by only varying the gate bias voltage V GS from 0 to 3 V. The strongest sensing response obtained from the device was around 0.547 mA ppb-1 at V GS = 3 V, which is 63.7% higher in comparison to the response achieved at 0 V which shows a sensing response of around 0.334 mA ppb-1. The current response depicts that the fabricated device is very sensitive and selective towards Hg2+ ions. Moreover, the detection limit of our sensor at 3 V was calculated around 6.21 ppt, which attributes to the strong field created between the gate electrode and the HEMT channel due to the presence of 1T metallic phase in synthesized MoS2, indicating that the lower detection limits are achievable in adequate strong fields.

DC Microgrids are vital in integrating renewable energy sources and supplying power to different critical and non-critical loads. However, this system's fundamental challenges are maintaining the voltage at the DC bus and equal current sharing among the parallel-connected converters even when the sources and loads are dynamic. This paper presents a novel non-linear discontinuous sliding mode controller for two Solar Photovoltaic, and a Battery Energy Storage System (BESS) based DC Microgrid. The proposed control technique precisely regulates the DC bus voltage and maintains equal load current sharing. Also, State of Charge (SoC) and Voltage-based charging and the discharging algorithm are implemented for the battery-interfaced bidirectional converter. In addition, the load shedding scheme for the non-critical loads is also implemented. The MATLAB simulation results ensure the DC Microgrid's desired operation under different operating conditions.

The GRAPES-3 experiment located in Ooty consists of an array of 400 plastic scintillator detectors spread over an area of 25000m2 and a large area (560 m2) muon telescope. Every day, the array records about 3 million showers induced by the interaction of primary cosmic rays in the atmosphere. One of the primary objectives of the experiment is to measure the energy spectrum and composition of the cosmic rays in the TeV-PeV energy range. However, some of the detected showers have cores outside the array. This fraction increases with energy due to the higher lateral spread of shower particles at higher energies. Identifying these events is thus crucial for accurate measurement of the cosmic ray energy spectrum. This work will describe simple cut based as well as machine learning based strategies for identifying and excluding such events and their impact on the cosmic ray energy spectrum as measured by the Bayesian unfolding technique.

Fast identification and classification of the faults in distribution network is a crucial task to ensure reliable power supply to the end user. This paper presents a protection scheme which makes use of Empirical Mode Decomposition of three phase current signals of a distribution network. The current signals measured at the substation bus over a moving window of one cycle are decomposed to obtain first level intrinsic mode function IMF1 and residue R1. A fault index which is nothing but the absolute mean of R1 is calculated for each phase and compared with a threshold to detect and categorize the type of fault. The proposed algorithm has been successfully tested on IEEE 13 bus system by varying the type of fault, fault incidence angle and fault location. The selectivity of the proposed scheme has been established by testing the algorithm with non faulty transients such as load switching and capacitor switching.

In this study, a novel and compact substrate integrated broadband Dielectric Resonator Antenna (DRA) excited by Substrate Integrated Coaxial Line (SICL) is presented. In comparison to the traditional non-planar DRA configuration, that requires mounting of a dielectric over the feed, the presented work provides a simple alternative by utilizing the same substrate of the SICL feed network making it planar. This eliminates the major challenge of a complex fabrication process in designing DRA. Two semi-circular rings fed by the top and middle layer of SICL feed line forms the resonating structure of the DRA, exhibiting a bandwidth of 550 MHz. The design procedure is shown to enhance the bandwidth to 1.3 GHz of the proposed antenna. The field distribution attained in the suggested Dielectric Resonator Antenna (DRA) has similarities to the HEM12δ mode of the standard cylindrical DRA. The proposed DRA achieves a broadside unidirectional beam with a gain of 5.5 dBi at 26 GHz.

The GRAPES-3 experiment located in Ooty consists of a dense array of 400 plastic scintillator detectors spread over an area of 25,000 m2 and a large area (560 m2) tracking muon telescope. Everyday, the array records about 3 million showers in the energy range of 1 TeV - 10 PeV induced by the interaction of primary cosmic rays in the atmosphere. These showers are reconstructed in order to find several shower parameters such as shower core, size, and age. High-energy showers landing far away from the array often trigger the array and are found to have their reconstructed cores within the array even though their true cores lie outside, due to reconstruction of partial information. These showers contaminate and lead to an inaccurate measurement of energy spectrum and composition. Such showers are removed by applying quality cuts on various shower parameters, manually as well as with machine learning approach. This work describes the improvements achieved in removal of such contaminated showers with the help of machine learning.

This paper proposes a novel notion of Adaptive Sliding mode based loss free resistor (ASLFR), to achieve the dual purpose of power factor correction and voltage regulation. The scheme serves itself as an efficient solution for single-stage PFC circuits applications. The work also provides a qualitative analysis to establish the expediency of the proposed ASLFR over the existing SLFR technique. A boost topology is chosen for implementation, to showcase the effectiveness of the scheme. Relevant results have been demonstrated to support the theoretical claims.

F1exible micro and nano sensors are a highly attractive option for the monitoring of physiological parameters like temperature, respiration rate, heartbeat, etc. in the healthcare field. Smart textiles and wearables are one of the most suitable ways in which vital parameters of a person can be monitored continuously without severely affecting the comfort and health of the person. In this paper, a textile based flexible sensor has been developed to create a thin wrist band which can be used to monitor the temperature of the person wearing it so as to detect alarming changes in temperature like in the case of fever or hypothermia. The constituent materials and the weaving pattern have been selected so as to facilitate temperature sensing with high precision. Through a series of experiments in a controlled environment, the optimal number of strands, optimal weaving pattern and the optimal length of the fabric are found by varying the aforementioned parameters and calculating the temperature coefficient of resistance (TCR). The readings obtained from the sensor do not fluctuate vividly with the passage of time, which indicates that the readings are stable. From the change in resistance the corresponding change in temperature (from the body temperature for which the fabric is calibrated for) is calculated on the basis of TCR.