Department of Electrical Engineering

Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

In this paper, we propose a new automated quality-aware electrocardiogram (ECG) heat classification method for effective diagnosis of ECG arrhythmias under unsupervised healthcare environments. The proposed method consists of three major stages: 1) the ECG signal quality assessment ({''}acceptable{''} or ``unacceptable{''}) based on our previous modified complete ensemble empirical mode decomposition and temporal features; 2) the ECG signal reconstruction and R-peak detection; and 3) the ECG beat classification including the ECG beat extraction, beat alignment, and normalized cross-correlation-based beat classification. The accuracy and robustness of the proposed method are evaluated using different normal and abnormal ECG signals taken from the standard MIT-BIH arrhythmia database. Evaluation results show that the proposed quality-aware ECG beat classification method can significantly achieve false alarm reduction ranging from 24\% to 93\% under noisy ECG recordings. The R-peak detector achieves the average Se = 99.67\% and positive predictivity (Pp) = 93.10\% and the average sensitivity (Se) = 99.65\% and Pp = 98.88\% without and with denoising approaches, respectively. Results further showed that the proposed ECG beat extraction approach can improve the classification accuracy by preserving the QRS complex portion and suppressing the background noises under acceptable level of noises. The quality-aware ECG beat classification methods achieve higher kappa values for the classification accuracies which can be consistent as compared with the heartbeat classification methods without the ECG quality assessment process.

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IEEE Sensors Journal

A new automated signal quality-aware ECG beat classification method for unsupervised ECG diagnosis environments

The power distribution networks can be classified as active/passive and stiff/weak based on the nature of loads and network impedances. As an alternative to the conventional iron- and-copper based passive transformer, a solid state transformer (SST) can be used for interfacing such distribution networks to the medium voltage AC grids. Although the power architectures of SST for distribution grids are studied in detail, the control schemes for SST considering the nature of network is yet to be explored. In this paper, the control aspects for the popular three-stage cascaded multilevel solid state transformer (CMSST) are studied for the following grid scenarios: (i) SST interfacing two stiff grids, (ii) SST interfacing a stiff grid and a weak grid, and (iii) SST interfacing a stiff grid with a passive network. In this context, an average model of the CMSST is developed by replacing the basic switching cell (H-bridge) with its equivalent average model. It is shown that the control aspects are network specific and are not interchangeable. © 2017 IEEE.

2017 IEEE Innovative Smart Grid Technologies - Asia: Smart Grid for Smart Community, ISGT-Asia 2017

Solid state transformer control aspects for various smart grid scenarios

State estimation of nonlinear stochastic system in the setting of event-based (EB) measurements is quite challenging, because the measurements are not available at each sampling period, but are available only when a certain pre-specified event occurs. Recently, a nonlinear EB state estimator using Sequential Monte-Carlo approach is proposed in [21], where the authors obtained a EB state estimator for a given threshold. In this work, the results of [21] are extended as follows. Firstly, an empirical relation between the EB threshold and the average communication rate is obtained. Then, the performance of the estimator is evaluated by comparing the approximate error covariance matrix with the posterior Cramér-Rao bound. In addition, the computational complexity is addressed using the equivalent flop measure. Finally, the effectiveness of the proposed approach is demonstrated using two simulation examples. © 2017 IEEE.

2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017

Nonlinear event-based state estimation using sequential Monte Carlo approach

An improved proportionate adaptive filter based on maximum correntropy criterion (IP-MCC) is proposed for identifying systems with variable sparsity in an impulsive noise environment. Utilization of the MCC mitigates the effect of the impulsive noise while improved proportionate concept exploits the underlying system sparsity to improve the convergence rate. Performance analysis of the proposed IP-MCC reveals that the steady-state excess mean square error (EMSE) of the proposed IP-MCC filter is similar to that of MCC filter. Extensive simulations demonstrate that the proposed IP-MCC outperforms state-of-the-art algorithms in terms of convergence rate and detailed complexity analysis reveals that IP-MCC requires much less computational effort. © 2018 Elsevier Inc.

Digital Signal Processing: A Review Journal

Improved proportionate-type sparse adaptive filtering under maximum correntropy criterion in impulsive noise environments

Proportionate-type normalized LMS (Pt-NLMS) family of adaptive filtering algorithms for sparse system identification pose significant implementation challenges due to their high computational complexity especially for real-time applications like network echo cancelation. In this paper, we make the first attempt to implement Pt-NLMS algorithms in hardware. Several reformulations are proposed to simplify the original Pt-NLMS algorithms, thereby making them amenable to real-time VLSI implementations and the reformulated algorithms referred as delayed μ-law proportionate LMS (DMPLMS) algorithm for white input and delayed wavelet MPLMS (DWMPLMS) for colored input are then implemented in hardware. Simulation studies demonstrate that the performance loss is very small for the proposed reformulations. We implemented the proposed designs considering 16-bit fixed point representation in hardware, and synthesis results show that the DMPLMS architecture with 30% increase in hardware over the state-of-the-art conventional delayed LMS architecture achieves 3 × improvement in convergence rate for white input and the DWMPLMS architecture with 70\% increase in hardware achieves 10 × improvement in convergence rate for correlated input conditions. © 1993-2012 IEEE.

IEEE Transactions on Very Large Scale Integration (VLSI) Systems

Algorithm and VLSI Architecture Design of Proportionate-Type LMS Adaptive Filters for Sparse System Identification

This paper presents an empirical wavelet transform (EWT) based approach to perform postmortem analysis of wide-area measurement (WAM) based signals. The commonly used empirical mode decomposition (EMD) has limitations such as mode mixing, sensitivity to noise, and sampling rate. The decomposition provided by EWT is more consistent as compared to EMD. The modes revealed by the EWT help in extracting dynamic patterns of different power system disturbances. The dynamic patterns extracted through EWT-based decomposition are further used as inputs to a data-mining tool known as random forest, to build a wide-area disturbance classifier (WADC) model. The efficient mode extraction quality of the EWT-based signal processing tool is analyzed for WAM data recorded on Northern Grid of Indian Power System. The performance of the WADC is validated on IEEE 39-bus New England test system. The results provide improved performance in terms of decomposition quality and classification accuracy. © 2005-2012 IEEE.

IEEE Transactions on Industrial Informatics

A New Approach to Power System Disturbance Assessment Using Wide-Area Postdisturbance Records

This study presents a new methodology for fault-induced line outage detection in the power transmission network. Pre-fault operating conditions and synchronised phasor measurements at all generator buses are used to accomplish this task. Initially, the proposed scheme divides the whole power system under study into different protection zones corresponding to generator bus (es). Furthermore, a new index termed as 'gain in momentum' (GIM) at each generator bus is used to identify the expected tripped region (ETR). This information helps in reducing the search space. Once the ETR is identified, online measured power flow of line connected to generator of ETR having maximum GIM is compared with the estimated post-outage power flow of the same line. The post-outage power flow is obtained using pre-outage line flow and line outage distribution factor. The aforementioned power flow comparison helps in identifying the tripped transmission line. The performance of the proposed scheme is validated on the IEEE-39 bus New England system and 246-bus North India Grid using the Power System Simulation for Engineering software. The test results indicate that the proposed scheme is highly effective in identifying the tripped line of a transmission system. © The Institution of Engineering and Technology.

Fulltext

IET Generation, Transmission and Distribution

Online detection of tripped transmission line to improve wide-area SA in power transmission system

Massive multiple input multiple output (MIMO) is the key technology in the 5G communication network. Blind source separation (BSS) plays an important role in MIMO communication when information about the transmitted signals or channel is not available. Independent component analysis (ICA) is one of the well-known BSS technique applied in MIMO wireless communication. Existing BSS techniques like ICA assumes number of receiving antennas to be greater than or equal to the number of transmit antennas and hence cannot be applied to multiple input single output (MISO) communication scenario, that happens during downlink massive MIMO communication. In single channel blind source separation (SCBSS) the source signals are retrieved from a single observed mixture (single channel or single receiving antenna) of the source signals. In this paper, we investigate the application of SCBSS to MISO communication system. Using ensemble empirical mode decomposition (EEMD), the MISO communication system is converted to a pseudo- MIMO system followed by the application of principal component analysis (PCA) and ICA algorithms to separate the transmitted signals. The algorithm is successfully applied to 2 × 1 MISO system and with a slight modification to n × 1 MISO system. Simulation results are provided to validate the performance of the algorithm. © 2017 IEEE.

IEEE Vehicular Technology Conference

Single channel blind source separation for MISO communication systems

This paper presents a new methodology to adaptively shift the dependability and security bias of the transmission system protection logic depending on the system state. Contingencies such as generator outage, line outage, and line fault can induce stressed system condition. Under stressed conditions, protection logic should be more biased toward security. Phasor measurement unit information is used at the system protection centre to estimate the system state. A data-mining model known as random forest is utilized to accomplish the task of state assessment. Two different protection logics are used to make the final relaying decision. The first protection logic is the existing distance relay and the second protection logic is based on wide area information. Both the protection logics are connected though logic gates to make the final relaying decision. The performance of the proposed scheme is validated on the IEEE-39 bus New England system and 246-bus Indian Northern Regional Power Grid system. The test results indicate that the proposed algorithm can help in shifting the dependability-security bias of the protection logic adaptively, which will help in mitigating cascaded outages in the power transmission system. © 2010-2012 IEEE.

IEEE Transactions on Smart Grid

A new adaptive dependability-security approach to enhance wide area back-up protection of transmission system

This paper presents radio frequency (RF) micro-electromechanical system-based 3- and 4-bit phase shifters using single-pole-four-throw (SP4T) and single-pole-eight-throw (SP8T) switches. The design is fabricated on 635∼μm alumina substrate using a surface micromachining process. SP4T and SP8T switches demonstrate measured return loss of &gt;16 dB, worst case insertion loss of 1.66 dB, and isolation of &gt;13.6 dB up to 40 GHz. Total area of the SP4T and SP8T switches is 0.98 mm2 and 1.66 mm2, respectively. Switches are capable of handling 1 W of incident RF power and can sustain up to 1 billion cycles at 85°C. Finally, 3- and 4-bit phase shifters deliver measured return loss of &gt;12 dB, average insertion loss of &lt;5.4 dB, and average phase error of 1.65° at 35 GHz. The total area of the phase shifter (4-bit) is 7.5 mm2, which is lowest reported till date. Reliability tests of phase shifters demonstrate &gt;1 billion cycles with 0.1 W of power in cold switching. In addition, phase shifters also worked satisfactory up to &gt;400 million cycles with 0.5 W of power at 85 °C in hot switching condition. Devices were enclosed within a low-cost package and characterized them systematically. © 1992-2012 IEEE.