Md. Ashfanoor Kabir

Denoising of ECG signals based on noise reduction algorithms in EMD and wavelet domains

Abstract This paper presents a new ECG denoising approach based on noise reduction algorithms in empirical mode decomposition (EMD) and discrete wavelet transform (DWT) domains. Unlike the conventional EMD based ECG denoising approaches that neglect a number of initial intrinsic mode functions (IMFs) containing the QRS complex as well as noise, we propose to perform windowing in the EMD domain in order to reduce the noise from the initial IMFs instead of discarding them completely thus preserving the QRS complex and yielding a relatively cleaner ECG signal. The signal thus obtained is transformed in the DWT domain, where an adaptive soft thresholding based noise reduction algorithm is employed considering the advantageous properties of the DWT compared to that of the EMD in preserving the energy in the presence of noise and in reconstructing the original ECG signal with a better time resolution. Extensive simulations are carried out using the MIT-BIH arrythmia database and the performance of the proposed method is evaluated in terms of several standard metrics. The simulation results show that the proposed method is able to reduce noise from the noisy ECG signals more accurately and consistently in comparison to some of the stateof-the-art methods.

Synchronous detection and digital control of Shunt Active Power Filter in power quality improvement

Power Quality means to maintain purely sinusoidal current wave form in phase with a purely sinusoidal voltage wave form. Power quality improvement using traditional compensation methods include many disadvantages like electromagnetic interference, possible resonance, fixed compensation, bulkiness etc. So power system and power electronic engineers need to develop adjustable and dynamic solutions using custom power devices. These power conditioning equipments use static power electronic converters to improve the power quality of distribution system customers. The devices include Active Power Filter (APF), dynamic voltage restorer (DVR) and Unified Power Quality Conditioner (UPQC). APF is a compensator used to eliminate the disturbances in current. There are basically two types of APFs: the shunt type and the series type. This paper examines the control of Shunt Active Power Filter (SAPF) from two different aspects: Synchronous Detection Method (SDM) and digital control based on instantaneous power theory (p-q theory). Simulation results using MATLAB SIMULINK demonstrates the application of these methods to the control of APF. Moreover, this work shows that digital control provides better power quality improvement than SDM.

Neural network based maximum power point tracking of photovoltaic arrays

Photovoltaic energy has become the most prospective source of renewable energy at this moment of energy crisis in the world. To utilize this energy efficiently a photovoltaic array should be used at its maximum power point (MPP) all the time. Therefore, introducing an effective technique of tracking MPP is of immense importance. There are various techniques to track MPP reported in several literatures. Among them artificial neural network based MPP tracking is of less concern. In this paper a novel technique of tracking MPP using backpropagation neural network is proposed. The proposed model is designed and simulated in Matlab/Simulink. The design considers the change in solar irradiance and ambient temperature successfully tracks the maximum power point more accurately and quicker than conventional perturb and observe based controller and even better than fuzzy logic based controller in these situations. The overall test results validate the efficiency of the model as well as the backpropagation neural network method which can be used in related research works.

Fuzzy logic driven adaptive PID controller for PWM based buck converter

This paper presents the design and construction of a fuzzy logic based proportional integral derivative (PID) controller for the control of a pulse width modulation (PWM)based dc-dc buck converter working in Continuous Conduction Mode(CCM). The converter operates at a switching frequency of 100 KHz. Computer simulation is done to fuzzify the inputs and their membership functions, express the inference rules linking the input and output variables and defuzzify the output parameter. This approach is simple as no linearized model of the buck converter is required. In the simulation results it is seen that the fuzzy logic based PID control technique provides robust control for non-linear power electronics variable switching structure like the ideal dc-dc buck converter. The practical model of the buck converter is next considered. From extensive experimentations for various parameter set and load disturbances, it is shown that the proposed adaptive Fuzzy logic driven PID controlled buck converter outperforms such non-adaptive PID controlled converters in terms of rise time, settling time and ripple voltage at the output response.

An ECG signal denoising method based on enhancement algorithms in EMD and Wavelet domains

This paper presents a new method based on enhancement algorithms in Empirical Mode Decomposition (EMD) and Discrete Wavelet Transform (DWT) domains for ECG signal denoising. Unlike the conventional EMD based ECG denoising methods that neglect a number of initial IMFs containing the QRS complex as well as noise, we propose a windowing method in EMD domain to filter out the noise from the initial IMFs without discarding them completely thus preserving the QRS complex. The comparatively cleaner ECG signal thus obtained from the EMD domain is employed to perform an adaptive soft thresholding in the DWT domain considering the advantageous properties of the DWT compared to EMD in preserving the energy and reconstructing the original ECG signal with a better time resolution. The performance of the proposed method is evaluated in terms of standard metrics by performing extensive simulations using the MIT-BIH arrhythmia database. The simulation results show that the proposed method is able to enhance the noisy ECG signals of different levels of SNR more accurately and consistently in comparison to some of the state-of-the-art methods.

Microcontroller based maximum power tracking of PV using stimulated annealing algorithm

In this paper, a completely new algorithm based on Stimulated Annealing technique for MPPT is proposed to optimize standalone PV panel operating point even under rapidly and significantly changing weather pattern. The proposed algorithm is as simple as traditional P&O and Hill-climbing algorithm, yet it can successfully encounter the oscillation problem and steady state error problem even under worst case scenario with efficiency more than 99.99%. The algorithm eliminates hardware complexity and can be implemented using programmable microcontrollers. This paper presents performance comparison of stimulated annealing algorithm with three of the most popular artificially intelligent algorithms such as fuzzy logic algorithm, particle swarm optimization algorithm and Genetic algorithm. Step by step procedure for practical implementation of the proposed algorithm is included at the later part of this paper.

Ćuk topology based single phase AC-DC converter wih low THD and high power factor

To topologies of single-phase Ćuk AC-DC converters with low input current THD and high input power factor are proposed. Instead of using a single phase rectifier followed by a boost DC-DC converter, or using a bridge rectifier with two diodes and two switches, the rectifiers input is chopped at high frequency during positive and negative cycles by a bi-directional switch in Ćuk conversion mode to get step-up/step-down AC-DC conversion. Total Harmonic Distortion (THD) of the input current of the proposed circuits with small input current filter is low. Input power factor and the efficiency of conversion of the circuits are high. The circuits exhibit such performance with variable loads at constant frequency switching. No additional control is required to achieve the advantages.

Input switched single phase buck and buck-boost AC-DC converter with improved power quality

Two new topologies of single-phase AC-DC converter using Buck and Buck-Boost conversion with low input current THD and high input power factor are proposed. Instead of using a single phase rectifier followed by a boost DC-DC converter, or using a bridge rectifier with two diodes and two switches, the rectifiers input is chopped at high frequency during positive and negative cycles by a single bi-directional switch to get step-up/step-down ac-dc conversion. Total Harmonic Distortion (THD) of the input current of the proposed circuit with small input current filter is low. Input power factor and the efficiency of conversion of the circuit are high. No additional control is required to achieve the advantages.

Boost and Buck topology based single phase AC-DC converters with low THD and high power factor

Two topologies of single-phase Buck and Boost AC-DC converters are presented. Instead of using a single phase rectifier followed by a boost dc-dc converter, or using a bridge rectifier with two diodes and two switches, the rectifiers input is chopped at high frequency during positive and negative cycles by a bi-directional switch in each of the Boost and Buck conversion mode to get step-up or step-down ac-dc conversion. Total Harmonic Distortion (THD) of the input current of the proposed circuits with small input current filter is low. Input power factor and the efficiency of conversion of the circuits are high. The circuits exhibit such performance with variable loads at constant frequency switching. No additional control is required to achieve the advantages.

Econometric modeling and forecasting of natural gas demand for power sector in Bangladesh

Natural gas is the principal indigenous resource for power generation in Bangladesh. Use of other conventional fossil fuels like petroleum and coal are quite insignificant with respect to the use of natural gas. The gas reserve of Bangladesh is depleting fast because of this heavy dependence on gas. Therefore, it is essential to have a realistic assessment of the gas demand pattern in the near future. In this paper the impacts of economic variables like gas price, per capita Gross Domestic Product (GDP) on gas demand were investigated by employing advanced econometric modeling technique. This research uses time series data for modeling the gas demand in Power sector and forecasting the demand up to 2025. Various statistical tests were employed to choose the correct functional form. Results show no significant impact of price on gas demand. Moreover, the forecast obtained from the analysis shows that the gas demand will increase rapidly in future. This research thus concludes that gas demand cannot possibly be controlled by price management and also emphasizes on strengthening the supply side to meet the growing gas demand in the near future.