Department of Electrical Engineering

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Particle filtration and concentration have great significance in a multitude of applications. Physical filters are nearly indispensable in conventional separation processes. Similarly, microfabrication-based physical filters are gaining popularity as size-based particle sorters, separators, and prefiltration structures for microfluidics platforms. The work presented here introduces a linear combination of obstructions to provide size contrast-based particle separation. Polystyrene particles that are captured along the crossflow filters are packed in the direction of the dead-end filters. Separation of polydisperse suspension of 5 μm and 10 μm diameter polystyrene microspheres is attained with capture efficiency for larger particles as 95%. Blood suspension is used for biocharacterization of the device. A flow induced method is used to improve particle capture uniformity in a single microchannel and reduce microgap clogging to about 30%. This concept is extended to obtain semiquantification obtained by comparison of the initial particle concentration to captured-particle occupancy in a microfiltration channel. © 2020 Author(s).

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Biomicrofluidics

Flow induced particle separation and collection through linear array pillar microfluidics device

A chemiresistive carbon monoxide (CO) gas sensor comprising of an organo-di-benzoic acidified zinc oxide (ODBA-ZnO) nanohybrid material is reported. The ODBA-ZnO hybrid material is prepared via a single-pot hydrothermal method. The electrical resistance of the drop-casted ODBA-ZnO film on interdigitated electrodes increases noticeably upon exposure to CO (5-500 ppm). The resistance increase is attributed to the formation of complex ions at the organic (ODBA)-inorganic (ZnO) interface in the presence of CO. The detailed CO sensing properties of the ODBA-ZnO nanohybrids reveal a remarkable selectivity to CO gas in comparison to other gases like CO2, H2S, and NH3 at 125 °C. The maximum response to 100 ppm of CO is observed to be 35% with the achieved selectivity to CO being 88%, which is the best reported CO selectivity result available in the literature to date. The ODBA-ZnO nanohybrid sensor takes nearly 91 s to reach the saturated response to 100 ppm of CO and nearly 175 s to recover from it in a synthetic air environment. A systematic study using field emission scanning electron microscopy, X-ray diffraction, energy-dispersive X-ray spectroscopy, nitrogen adsorption-desorption tests, and thermogravimetric analysis reveals that introduction of an organic moiety (ODBA) to ZnO played a key role in achieving improved selectivity and sensitivity toward CO. The present work provides a simple route for fabricating the ODBA-ZnO sensor to achieve better selectivity and sensitivity to CO gas at a relatively low temperature (125 °C). © 2020 American Chemical Society.

Journal of Physical Chemistry C

Organo-di-benzoic-acidified ZnO Nanohybrids for Highly Selective Detection of CO at Low Temperature

This paper presents detection of broken rotor bar fault using Stockwell transform of the stator current signals. The transform gives complex two-dimensional information pertaining to time and frequency. Entropy of the matrix with respect to time domain has been proposed as the fault detection parameter. Entropy is found to be useful for the detection as well as for the estimation of the severity of broken rotor bar faults. The results have been compared with the energy of the matrix. The results show that energy can only detect the fault unlike entropy. Thus, entropy can be used as a fault diagnostic parameter. The results have been validated on the experimentally recorded current signals for five different load conditions; from no-load to full-load. © 2020 IEEE.

9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020

Entropy-based broken rotor-bar fault detection and estimation of its severity in a three-phase induction motor

Compression of multimedia content is an important processing step and backbone of real life applications in terms of optimum resource utilization in transmission and storage. It is an established field of research with very little scope for further improvement in achieved compression through customary coding-based compression techniques. Consequently, non-customary compression methods have become an important area for future research. Based on the principle ‘Any information that can be restored can be compressed’, we propose a novel spectrum-based image compression technique to further reduce the data footprint with satisfactory quality metric for images. We first blur the image with a point spread function (PSF) determined using frequency content of the given image. Blurring increases the DC component in the image, which in turn gets further compressed compared with original image by DCT-based JPEG compression. To recover the image, we perform deconvolution using the known blur PSF. Results obtained show further improvement of 20 - 30 % in achieved compression with respect to original JPEG compressed image with satisfactory quality of recovered image. © 2020, Indian Academy of Sciences.

Sadhana - Academy Proceedings in Engineering Sciences

A novel non-customary method of image compression based on image spectrum

Conventionally, the point spread function (PSF) is understood as a characteristic function of any optical system. It captures the information about the amount of blur present along all the directions for a point in the scene. However, the dependence of blur on the PSF is in the form of convolution for any object other than a point source present in the scene and hence their relationship is less explicit. The authors propose a blur parameter locus curve (BPLC) as a system representation which has a one to one relationship with blur. BPLC simply is a chart of blur amounts in all directions of a given PSF with respect to the selected measurement function. They further characterise the PSF by decomposing the variation of BPLC across all directions based on the study performed for different possible forms of the blur kernels. Such decomposition provides powerful tools for various analysis. As PSF can be anisotropic, the computation of BPLC becomes an essential intermediate step to obtain the scale map as at the same scale, blur is different in different directions. Furthermore, they demonstrate the use of BPLC to obtain other system characteristics function such as PSF. © The Institution of Engineering and Technology 2019.

IET Image Processing

Blur parameter locus curve and its applications

Equilibrium-independent passive-short (EIPS) systems are a class of systems that satisfy a passivity-like dissipation inequality with respect to any forced equilibria with non-positive passivity indices. This paper presents a geometric approach for finding a passivizing transformation for such systems, relying on their steady-state input-output relation and the notion of projective quadratic inequalities (PQIs). We show that PQIs arise naturally from passivity-shortage characteristics of an EIPS system, and the set of their solutions can be explicitly expressed. We leverage this connection to build an input-output mapping that transforms the steady-state input-output relation to a monotone relation, and show that the same mapping passivizes the EIPS system. We show that the proposed transformation can be implemented through a combination of feedback, feed-through, post- and pre-multiplication gains. Furthermore, we consider an application of the presented passivation scheme for the analysis of networks comprised of EIPS systems. Numerous examples are provided to illustrate the theoretical findings. IEEE

IEEE Transactions on Automatic Control

A Geometric Method for Passivation and Cooperative Control of Equilibrium-Independent Passivity-Short Systems

This paper reports the effect of the design parameters of a solidly mounted film bulk acoustic resonator (SMFBAR) for better gas sensing performance. The electrical equivalent circuit of the proposed device has been developed with the help of a Butterworth Van-Dyke (BVD) circuit. The electro-mechanical response of the SMFBAR has been obtained with the help of 3-D finite element method (FEM) analysis. The analytical modeling and FEM simulation results are compared. The physical parameters of the proposed design such as piezoelectric layer material, its thickness, active area of the device and sensing layer thickness affecting the characteristics of the SMFBAR have been investigated in detail. To achieve enhanced sensitivity, the variation of square active area has been analysed with one side dimension ranging from 700 μm to 300 μm. Gas sensing performance of the proposed sensor is tested by exposing toluene gas concentration ranging from 0 ppm to 500 ppm and enhanced sensitivity of 20 kHz/ppm has been achieved and reported. Also, it is reported that the variation in ratio of electrode layer thickness to piezoelectric layer thickness results in improvement of coupling coefficient (keff 2) up to 7.46%. © 2019, The Minerals, Metals & Materials Society.

Journal of Electronic Materials

Design, Analysis and Finite Element Modeling of Solidly Mounted Film Bulk Acoustic Resonator for Gas Sensing Applications

Automatic recognition of modulation scheme in blind environment plays a key role in many communication applications. A hierarchical and local density (HLD) approach is proposed to classify eight modulation schemes in a two stage process. In the first stage, the domain of modulation schemes (FSK, ASK, PSK, and QAM) is identified. FSK is identified based on feature extracted through complex envelope of downconverted signal. ASK scheme is identified using linear regression error. PSK and QAM modulation schemes are recognized based on the ratio of sixth and fourth order cumulant. In the latter stage, the order of modulation (ASK, PSK, and QAM) is classified through its respective ideal constellation points. HLD can correctly identify 2ASK, 4ASK, and QPSK modulation schemes in AWGN channel above 8 dB SNR and the other modulation schemes (8ASK, 8PSK, 16QAM, and 64QAM) above 16dB SNR. HLD is implemented in NI labVIEW and validated on the signals generated through PXIe-5673 and received using NI PXIe-5661. The proposed HLD classifier does not require any training to set thresholds as compared to more complex SVM, KNN, and Naive Bayes Classifier based techniques and shows an improved accuracy. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Wireless Personal Communications

Blind Signal Modulation Recognition through Density Spread of Constellation Signature

Deep learning (DL) is a newly addressed area of research in the field of modulation classification. In this letter, a constellation density matrix (CDM) based modulation classification algorithm is proposed to identify different orders of ASK, PSK, and QAM. CDM is formed through local density distribution of the signal's constellation generated using LabVIEW for a wide range of SNR. Two DL models, ResNet-50 and Inception ResNet V2 are trained through color images formed by filtering the CDM. Classification accuracy achieved demonstrates better performance compared to many existing classifiers in the literature. © 1997-2012 IEEE.

IEEE Communications Letters

Automatic modulation classification based on constellation density using deep learning

In this article, we study the physical layer security of free-space optical (FSO) communications under different eavesdropping scenarios. More specifically, the secrecy performance of FSO communication employing intensity modulation/direct detection detection is analyzed for the well-established Málaga channels. Three different realistic scenarios of eavesdropping are considered by assuming different placement locations for the eavesdropper in the paper. Novel expressions for the average secrecy capacity (ASC) and secrecy outage probability (SOP) are derived for the considered scenarios, and useful insights are also provided through asymptotic analysis. The results show: (1) When the eavesdropper is placed near the transmitter, atmospheric condition imposes a less significant impact on secrecy performance; (2) Certain level of correlation can potentially enhance the secrecy performance for FSO communications; (3) The correlation imposes opposite impacts on the ASC and SOP of FSO communications; and the secrecy performance metrics exhibit a non-monotonic impact with the increase of correlation; (5) When the correlation of the FSO links is too small or too large (i.e., the correlation parameter around 0 or 1), the correlation plays a more significant impact on secrecy performance; and (6) The asymptotic slope of the SOP is 0.5 for all eavesdropping scenarios under practical FSO channels. © 2009-2012 IEEE.