Anita Agrawal

Investigation of Microelectromechanical Switches for Next Generation DC Power Distribution System

Abstract This paper investigates the application of microelectromechanical system (MEMS) switches for DC power distribution system. Traditional electromechanical switches, solid state switches and solid state switch array are studied and simulated to understand their characteristics. Performance and characteristics of MEMS switches are reviewed and identified that electrostatically actuated MEMS switches are suitable for DC power applications. Scalable total cross tied (TCT) array configuration using MEMS switches has been proposed. The proposed configuration is suitable for variable voltage/current rating. Arc-less behavior of the switch configuration is analyzed using modified Paschen’s curve. 400 V/6 A system is considered for the simulation and comparative study. The simulated result of the proposed MEMS switch array configuration is compared with the traditional switches. The comparative study shows that the proposed switch array configuration gives better performance in terms of voltage drop, leakage current, power loss, arc and size. This can be used in DC power system protection, circuit breaking, battery protection and smart grid load switching applications.

HexaMob—A Hybrid Modular Robotic Design for Implementing Biomimetic Structures

Modular robots are capable of forming primitive shapes such as lattice and chain structures with the additional flexibility of distributed sensing. The biomimetic structures developed using such modular units provides ease of replacement and reconfiguration in co-ordinated structures, transportation etc. in real life scenarios. Though the research in the employment of modular robotic units in formation of biological organisms is in the nascent stage, modular robotic units are already capable of forming such sophisticated structures. The modular robotic designs proposed so far in modular robotics research vary significantly in external structures, sensor-actuator mechanisms interfaces for docking and undocking, techniques for providing mobility, coordinated structures, locomotions etc. and each robotic design attempted to address various challenges faced in the domain of modular robotics by employing different strategies. This paper presents a novel modular wheeled robotic design - HexaMob facilitating four degrees of freedom (2 degrees for mobility and 2 degrees for structural reconfiguration) on a single module with minimal usage of sensor-actuator assemblies. The crucial features of modular robotics such as back-driving restriction, docking, and navigation are addressed in the process of HexaMob design. The proposed docking mechanism is enabled using vision sensor, enhancing the capabilities in docking as well as navigation in co-ordinated structures such as humanoid robots.

An FEM Study of the Electrothermal Properties of Microelectrical Contacts for Application in the Design of Arcless Switches

This paper discusses the electrothermal characteristics of microelectrical contacts for arcless switching. The 3-D microelectrical contact suitable for dc power-switching application is considered. The important parameters for the design of an arcless microelectrical contact are identified. The ON-state contact resistance and the temperature are calculated and simulated using an Finite Element Method (FEM) tool. In order to design an arcless switching contact, the simulation-based steady-state and transient temperature distributions are estimated. The OFF-state capacitance and the electric field distribution are calculated and simulated for the arcless microelectrical contact. The analysis is carried out for the materials Al, Cu, Au, and Pt. The power ratings of the arcless microelectrical contact are identified. These results can be considered while designing an arcless electrical contact for microswitches, relays, and circuit breakers.

Effect of electric field on electrical breakdown arc behavior of micro contact gaps: A 3D approach

This paper presents the electric breakdown arc behavior of micro electrical contact with respect to electric field across contact gap. The breakdown electric field characteristics of Al, Cu, Fe, Ni, and Pt are reported. The 3D plane-plane micro electrical contact has been considered and maximum electric field is analyzed mathematically. Also the considered electrode has been simulated using COMSOL FEA tool for the contact gap from 1 to 30μm. The influence of contact gap and contact size has been simulated and results are compared with the numerical results. The arc behavior of the micro electrical contact for various voltages and contact size are simulated and results are presented. It is found that increasing the size of micro electrical contact reduces the electric field considerably and it can switch higher voltage without arcing. The effect of thickness on electric field and off-state isolation of micro electrical contact is reported. These results can be considered while designing arc-less micro electrical switches, micro relays and micro circuit breakers which can be applicable to the future DC electric power distribution and protection systems.

Modeling and Analysis of Scalable Arcless Micromechanical Switch for Battery Powered Electrical System

Objective: In this paper, electrostatically actuated micromechanical switch for battery powered electrical system has been presented. An electrostatically actuated micromechanical switch has been designed and the electromechanical characteristics have been discussed. Methods: The switching characteristics, power loss and leakage current of the switch have been obtained for 12 V/0.2 A electrical system. In order to meet the high power rating, the designed arcless micromechanical switches have been connected in a scalable cross-tied array configuration and the switching characteristics were obtained for 144 V/3 A electrical system. Result: The arc existing parts of the micromechanical switch have been identified and the arcless switching has been discussed. The reliability of the switch has been presented based on electromechanical behavior, arcless switching and scalability. The discharging characteristics of battery have been obtained for the circuit having solid-state and micromechanical switch. Conclusion: The result shows significant improvement in the power loss, battery discharging characteristics and is promising application for battery operated electrical system. A R T I C L E H I S T O R Y Received: April 21, 2018 Revised: June 09, 2018 Accepted: June 14, 2018 DOI: 10.2174/1876402910666180622094024

Ischemic stroke lesion segmentation using stacked sparse autoencoder

Automatic segmentation of ischemic stroke lesion volumes from multi-spectral Magnetic Resonance Imaging (MRI) sequences plays a vital role in quantifying and locating the lesion region. Most existing methods mainly rely on designing hand-crafted features followed by a classifier model for ischemic stroke lesion segmentation. Design of these features requires complex domain knowledge and often lacks the ability to differentiate between the stroke lesions and the normal classes. In this work, we propose an unsupervised featured learning approach based on stacked sparse autoencoder (SSAE) framework for automatically learning the features for accurate segmentation of stroke lesions from brain MR images. A deep architecture is designed using sparse autoencoder (SAE) layers, followed by support vector machine (SVM) classifier for classifying the patches into normal or lesions. We validated our approach on a publicly available Ischemic Stroke Lesion Segmentation (ISLES) 2015 dataset, with a mean precision of 0.968, mean dice coefficient (DC) of 0.943, mean recall of 0.924 and mean accuracy of 0.904. The experimental results show that our proposed approach significantly outperforms the state-of-the-art methods in terms of precision, DC, and recall. Quantitative evaluation was carried out and compared with the existing approaches, which demonstrates that the proposed method is 25.71%, 36.67%, and 16.96% higher in terms of precision, DC and recall values, respectively. The unsupervised features learned via SSAE framework performs better than the hand-crafted features and can be easily trained on large datasets.

Time-frequency based feature extraction for the analysis of vibroarthographic signals

Abstract In this study, we propose to develop a computer-aided diagnostic (CAD) system based on time-frequency analysis for the diagnosis of knee-joint disorders. Two methodologies based on nonstationary signal processing techniques have been proposed. We propose to use smoothed pseudo Wigner–Ville distribution (SPWVD) and a modified version of Hilbert–Huang transform (HHT) for the analysis of vibroarthographic (VAG) signals. Traditional HHT consists of empirical mode decomposition (EMD) for computing intrinsic mode functions (IMFs) and Hilbert transform (HT). But we propose to use complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) for computing IMFs. The time-frequency representation of the proposed methods is considered as a time-frequency image. Statistical features such as mean, standard deviation, skewness and kurtosis are extracted. A pattern classification is carried out using Least square support vector machine (LS-SVM) to compare performance. Results concluded that highest classification accuracy of 88.76% was obtained by features extracted from CEEMDAN-HHT.

SQ-BOT - a modular robot prototype for self-reconfiguring structures

The modular robotics offers various advantages in relative to traditional robotic solutions for real world scenarios due to application specific nature and limited flexibilities of later. The low cost robust capabilities of the modular systems inspired researchers of swarm robotics, automation etc. to research modular robotics for developing affordable and capable systems to various applications in surveillance, disaster management etc. The research work in modular robotics so far is limited to laboratory prototyping and the development is yet to take complete form for real world applications. In this paper, a design of modular unit named “SQ-BOT” suitable for practical applications is proposed along with model simulations and hardware experiments.

Towards EMG Based Gesture Recognition for Indian Sign Language Interpretation Using Artificial Neural Networks

There are several techniques of data measurement for gesture recognition, with applications ranging from prosthetic or autonomous control to human-computer interfacing. Most of the typical techniques depend on image processing, and might face portability hurdles. This paper discusses a method to classify gestures based on the surface EMG (sEMG) readings, thereby allowing user portability. These sEMG readings acquired from the upper forearm provide a direction towards gesture recognition for Indian Sign Language (ISL) interpretation. An Artificial Neural Network (ANN) based on the Scaled Conjugate Gradient (SCG) assisted learning is used to process the data and classify gestures with an accuracy of 97.5 %. The training involved 120 samples corresponding to four distinct wrist gestures. Additionally, the foundations for user-independent adaptability have been laid in this paper.

Vehicle Regulatory System using wireless Vehicle Terminal Unit

The proposed approach of Vehicle Regulatory System (VRS) using wireless vehicle terminal unit (VTU)* is based on communication between a Vehicle Terminal Unit and the Outside Terminal (OT). The VTU is placed in the vehicle and sends continuously vehicle basic information code through radio frequency signals in all directions. These signals are captured by the OT (which is connected to outside world) and the records of all Vehicle Terminal Units which are in its communication range are stored in its database. The VTU will consist of basic information of the said vehicle like chassis no, engine no, registration no, validity of registration, type of vehicle etc. This information is stored in the memory (read only) of the VTU at the time of registration in continuous encrypted way. Communication or linking of this system is based on radio frequency signal communication in free license band of frequency (2.41 to 2.49 GHz) and application based communication protocol. The range of operation is about 200 meters. It supports different activities of the authorized vehicle regulatory agencies of that region. This system helps to keep track of the road vehicle movements in specific area. It will create new vision in the field of vehicle monitoring and controlling system for next generation applications.