Papers by Abdul Rahim Abdullah
Journal of Telecommunication, Electronic and Computer Engineering, 2016
Electromyography (EMG) signal is non-stationary signal and highly complex time and frequency char... more Electromyography (EMG) signal is non-stationary signal and highly complex time and frequency characteristics. Fast-Fourier transform common technique in signal processing involving EMG signal. However, this technique has a limitation to provide the time-frequency information for EMG signals. This paper presents the analysis of EMG signal of the variable lifting height and mass of load between the four subjects selected in manual lifting by using spectrogram. Spectrogram is one of the time-frequency representation (TFR) that represents the threedimensional of the signal with respect to time and frequency in magnitude presentations. The manual lifting tasks is based on manual lifting of 5 kg and 10 kg load that performed by the right biceps brachii at lifting height of 75 cm and 140 cm. Four from ten healthy volunteers in fresh condition is selected into this comparison of subject performance tasks with their raw data collections. The raw data of EMG signals were then analyzed using M...
The need of sustainable energy without any interference such as harmonics for mobility equipment ... more The need of sustainable energy without any interference such as harmonics for mobility equipment became the major challenge in selecting suitable energy storage device. The rechargeable batteries become alternatives due to its ability to store and restore the energy that will maintain the continuity of the power supply. However, without proper monitoring of the battery performance, the condition of both equipment and battery itself can be worsening. This paper proposes a new time-frequency distribution (TFD) techniques which are spectrogram based on experimentation of lead acid (LA) battery. Estimation of parameters such as instantaneous of root means square voltage (V ), instantaneous direct current voltage (V ) and RMS DC instantaneous alternating current voltage (V ) are extracted from a time-frequency representation (TFR) AC through the charging and discharging characteristics of the batteries. Experiment is conducted based on three different LA battery with fixed nominal voltag...
Journal of Telecommunication, Electronic and Computer Engineering, 2016
Time-frequency representation of a signal has been widely used in various research areas to analy... more Time-frequency representation of a signal has been widely used in various research areas to analyze non-stationary signals (ie. electromyography (EMG) signals). However, due to the high computational complexity of certain time-frequency distribution techniques, the application of these techniques in the analysis of long duration EMG signals is not suitable. To overcome this problem, muscle contraction segmentation is essential to process the existed EMG signals, since not all of the EMG signal contains valid information to be analyzed. Thus, this paper presents an algorithm to automatically detect and segment the muscle contractions existed in EMG signal during long duration recordings. Surface EMG signals were collected from biceps branchii muscle of ten subjects during manual lifting. Subjects were required to lift a 5 kg load mass with lifting height of 75 cm until experiencing fatigue. The utilization of instantaneous energy of EMG is used to estimate the presence of first muscl...
Journal of Telecommunication, Electronic and Computer Engineering, 2018
Electromyography (EMG) is one of the most commonly used tools to study human muscle condition. Pa... more Electromyography (EMG) is one of the most commonly used tools to study human muscle condition. Past researchers have introduced various techniques from time distribution (TD), frequency distribution (FD) and timefrequency distribution (TFD) to extract information from this EMG signal. However, due to the complex characteristics of the EMG signal itself, TFD such as spectrogram has been widely used as it can provide both temporal and spectral information. However, since spectrogram has a fix window size, there exists a dilemma of resolution, where the too narrow window will result in a poor frequency resolution, and a too wide window will cause poor time resolution. Thus, this study aims to select the best window size to be used with spectrogram to monitor human muscle electrical activity during core lifting task. Four electrodes were placed over different types of muscles, which are the right and left biceps branchii (BB), and right and left erector spinae (ES). In this study, six w...
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2020
This paper introduces the accurate identification of harmonic sources in the power distribution s... more This paper introduces the accurate identification of harmonic sources in the power distribution system using time-frequency distribution (TFD) analysis, which is S-transform. The S-transform is a very applicable method to represent signals parameters in time-frequency representation (TFR) such as TFR impedance (ZTFR) and the main advantages of S-transform it can provide better frequency resolution for low frequency components and also offers better time resolution for high-frequency components. The identification of multiple harmonic sources are based on the significant relationship of spectral impedances (ZS) that extracted from the ZTFR, consist of the fundamental impedance (Z1) and harmonic impedance (Zh). To verify the accuracy of the proposed method, MATLAB simulations carried out several unique cases on IEEE 4-bus test feeder cases. It is proven that the proposed method is superior, with 100% correct identification of harmonic source location. It is proven that the method is accurate, fast and cost-efficient to localize harmonic sources in the power distribution system.
Bulletin of Electrical Engineering and Informatics, 2021
This paper proposes a comparison of machine learning (ML) algorithm known as the k-nearest neighb... more This paper proposes a comparison of machine learning (ML) algorithm known as the k-nearest neighbor (KNN) and naïve Bayes (NB) in identifying and diagnosing the harmonic sources in the power system. A single-point measurement is applied in this proposed method, and using the S-transform the measurement signals are analyzed and extracted into voltage and current parameters. The voltage and current features that estimated from time-frequency representation (TFR) of S-transform analysis are used as the input for MLs. Four significant cases of harmonic source location are considered, whereas harmonic voltage (HV) and harmonic current (HC) source type-load are used in the diagnosing process. To identify the best ML, the performance measurement of the proposed method including the accuracy, precision, specificity, sensitivity, and F-measure are calculated. The sufficiency of the proposed methodology is tested and verified on IEEE 4-bust test feeder and each ML algorithm is executed for 10...
International Journal of Electrical and Computer Engineering (IJECE), 2020
This paper outlines research conducted using bilinear time-frequency distribution (TFD), a smooth... more This paper outlines research conducted using bilinear time-frequency distribution (TFD), a smooth-windowed wigner-ville distribution (SWWVD) used to represent time-varying signals in time-frequency representation (TFR). Good time and frequency resolutions offer superiority in SWWVD to analyze voltage variation signals that consist of variations in magnitude. The separable kernel parameters are estimated from the signal in order to get an accurate TFR. The TFR for various kernel parameters is compared by a set of performance measures. The evaluation shows that different kernel settings are required for different signal parameters. Verification of the TFD that operated at optimal kernel parameters is then conducted. SWWVD exhibits a good performance of TFR which gives high peak-to-side lobe ratio (PSLR) and signal-to-cross-terms ratio (SCR) accompanied by low main-lobe width (MLW) and absolute percentage error (APE). This proved that the technique is appropriate for voltage variation ...
International Journal of Electrical and Computer Engineering (IJECE), 2017
This paper presents a utilization of improved Gabor transform for harmonic signals detection and ... more This paper presents a utilization of improved Gabor transform for harmonic signals detection and classification analysis in power distribution system. The Gabor transform is one of time frequency distribution technique with a capability of representing signals in jointly time-frequency domain and known as time frequency representation (TFR). The estimation of spectral information can be obtained from TFR in order to identify the characteristics of the signals. The detection and classification of harmonic signals for 100 unique signals with numerous characteristic of harmonics with support of rule-based classifier and threshold setting that been referred to IEEE standard 1159 2009. The accuracy of proposed method is determined by using MAPE and the outcome demonstrate that the method gives high accuracy of harmonic signals classification. Additionally, Gabor transform also gives 100 percent correct classification of harmonic signals. It is verified that the proposed method is accura...
International Journal of Integrated Engineering, 2019
This paper presents the application of spectrogram with K-nearest neighbors (KNN) and Support Vec... more This paper presents the application of spectrogram with K-nearest neighbors (KNN) and Support Vector Machine (SVM) for window selection and voltage variation classification. The voltage variation signals such as voltage sag, swell and interruption are simulated in Matlab and analyzed in spectrogram with different windows which are 256, 512 and 1024. The variations analyzed by spectrogram are displayed in time-frequency representation (TFR) and voltage per unit (PU) graphs. The parameters are calculated from the TFR obtained and be used as inputs for KNN and SVM classifiers. The signals obtained are then added with noise (0SNR and 20SNR) and used in classification. The tested data contain voltage variation signals obtained using the mathematical models simulated in Matlab and the signals added with noise. Classification accuracy of each window by each classifier is obtained and compared along with the TFR and voltage PU graphs to select the best window to be used to analyze the best window to be used to analyze the voltage variation signals in spectrogram. The results showed window 1024 is more suitable to be used.
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2018
In this paper, the power quality (PQ) disturbance which is the voltage variations consist of volt... more In this paper, the power quality (PQ) disturbance which is the voltage variations consist of voltage swell, sag and interruption are model and analyze. Different types of voltage variations PQ disturbances models are developed and created by using MATLAB/Simulink as well as mathematical models. The mathematical and Simulink model are used to compare in terms of time-frequency representation (TFR). The Simulink models include shutting down enormouscapacities from system to resemble voltage swell, large loads energizing and three-phase fault to simulate voltage sag as well as implementing permanent three-phase fault to simulate voltage interruption. The signals generated are analyzed by using linear time-frequency distribution (TFD). The signal parameters such as root mean square voltage (Vrms), total harmonic distortion (THD) and power value are estimated from the TFR to identify the characteristics of the voltage variation. The results of analysis on the PQ disturbance waveforms generated are identical to the actual real-time PQ signals and the models can be modified to any desired situation respectively. The PQ waveforms obtained are suitable to be further analyzed.
Jurnal Teknologi, 2019
This research presents the analysis of battery charging and discharging signals using spectrogram... more This research presents the analysis of battery charging and discharging signals using spectrogram, and S-transform techniques. The analysed batteries are lead acid (LA), nickel-metal hydride (Ni-MH), and lithium-ion (Li-ion). From the equivalent circuit model (ECM) simulated using MATLAB, the constant charging and discharging signals are presented, jointly, in time-frequency representation (TFR). From the TFR, the battery signal characteristics are determined from the estimated parameters of instantaneous means square voltage (VRMS (t)), instantaneous direct current voltage (VDC (t)), and instantaneous alternating current voltage (VAC (t)). Hence, an equation for battery remaining capacity as a function of estimated parameter of VAC (t) using curve fitting tool is presented. In developing a real-time automated battery parameters estimation system, the best time-frequency distribution (TFD) is chosen in terms of accuracy of the battery parameters, computational complexity in signal p...
Computers, 2018
Features extracted from the electromyography (EMG) signal normally consist of irrelevant and redu... more Features extracted from the electromyography (EMG) signal normally consist of irrelevant and redundant features. Conventionally, feature selection is an effective way to evaluate the most informative features, which contributes to performance enhancement and feature reduction. Therefore, this article proposes a new competitive binary grey wolf optimizer (CBGWO) to solve the feature selection problem in EMG signals classification. Initially, short-time Fourier transform (STFT) transforms the EMG signal into time-frequency representation. Ten time-frequency features are extracted from the STFT coefficient. Then, the proposed method is used to evaluate the optimal feature subset from the original feature set. To evaluate the effectiveness of proposed method, CBGWO is compared with binary grey wolf optimization (BGWO1 and BGWO2), binary particle swarm optimization (BPSO), and genetic algorithm (GA). The experimental results show the superiority of CBGWO not only in classification perfor...
IET Generation, Transmission & Distribution, 2017
This study presents two different methods under uniform and non-uniform pollution layer in order ... more This study presents two different methods under uniform and non-uniform pollution layer in order to measure and calculate the leakage current (LC) of silicone rubber insulators. Experimental test for evaluating the LC analysis of polluted insulator have been done in a laboratory clean fog chamber. The electric field and potential distributions were obtained from finite element method software for 3D models. The mathematical background and circuit theory are described in details by a section of insulator and using the extended form factor formula. The surface conductivity used in the calculations was extracted from the measured LC after wetting rate. LC characteristics under 1 : 1, 1 : 2, 1 : 5 and 1 : 10 ratios of top to bottom surface salt deposit density on polymeric insulators are studied. To verify the proposed models of this study, the results of experimental data and two other approaches are compared with together before dry-band formation. Moreover, a dynamic LC model under uniform pollution layer has been introduced and extended in order to calculate the LC when the formation of dry-bands along the insulator surface occurs. The dynamic model is drawn from experimental data and measured surface conductivity.
International Journal of Electronics and Electrical Engineering, 2016
Nowadays, voltage source inverter (VSI) is frequently used in power electronics system. This is d... more Nowadays, voltage source inverter (VSI) is frequently used in power electronics system. This is due to its ability that can offer higher efficiency, high torque, simpler control system and improved power output. Thus, to ensure safety and reliability of a system, the development of appropriate fault detection technique for faults analysis is a must. This paper proposes S-transform which is timefrequency distribution (TFD) for analyzing VSI signal to detect and identify switches and types of faults. By using the TFD, the faults signal is translated into time-frequency representation (TFR) and then, parameters of the signal are estimated from the TFR. The signal parameters are such as instantaneous of rms current, rms fundamental current, average current, total waveform distortion (TWD), total harmonic distortion (THD) and total non-harmonic distortion (TnHD). Based on the signal parameters, the characteristics of the faults are calculated and used as input for faults detection and classification system. At the end of this research, the results show that the proposed TFD give better analysis for switches faults parameters estimation and suitable for detection and identification system.
Applied Mechanics and Materials, 2015
Switches fault in power converter has become compelling issues over the years. To reduce cost and... more Switches fault in power converter has become compelling issues over the years. To reduce cost and maintenance downtime, a good fault detection technique is an essential. In this paper, the performance of STFT and S transform techniques are analysed and compared for voltage source inverter (VSI) switches faults. The signal from phase current is represented in jointly time-frequency representation (TFR) to estimate signal parameters and characteristics. Then, the degree of accuracy for both STFT and S transform are determined by the lowest value of mean absolute percentage error (MAPE). The results demonstrate that S transform gives better accuracy compare to STFT and is suitable for VSI switches faults detection and identification system.
Applied Mechanics and Materials, 2015
Batteries are essential components of most electrical devices and one of the most important param... more Batteries are essential components of most electrical devices and one of the most important parameters in batteries is storage capacity. It represents the maximum amount of energy that can be extracted from the battery under certain specified condition. This paper presents the analysis of charging and discharging battery signal using periodogram. The periodogram converts waveform data from the time domain into the frequency domain and represents the distribution of the signal power over frequency. This analysis focuses on four types of batteries which are lead-acid (LA), lithium-ion (Li-ion), nickel-cadmium (Ni-Cd) and nickel-metal-hydride (Ni-MH). This paper used battery model from MATLAB/SIMULINK software and the nominal voltage of each battery is 6 and 12V while the capacity is 10 and 20Ah, respectively. The analysis is done and the result shows that varying capacity produce different power at a frequency and voltage at DC component.
Applied Mechanics and Materials, 2015
Open-switch and short-switch in a three-phase voltage source inverter (VSI) have a possibility to... more Open-switch and short-switch in a three-phase voltage source inverter (VSI) have a possibility to fault due to problems of switching devices.Any failure of the system in these applications may incur a cost and risk human live. Therefore, knowledgeon the fault mode behaviour of an inverter is extremely important from the standpoint of system design improvement, protection and fault detection. This paper presents detailed simulation results on condition monitoring and fault behaviour of VSI. The results obtained from the developed monitoring system allows user to identify the fault current. The developed system showed the capability in detecting the performance of VSI as well as identifying the characteristics of type of faults. This system provides a precaution and early detection of fault, thus reduces high maintenance cost and prevent critical fault from happening.
Applied Mechanics and Materials, 2015
Voltage source inverter (VSI) plays an important roles in electrical drive systems. Consistently,... more Voltage source inverter (VSI) plays an important roles in electrical drive systems. Consistently, expose to hash environmental condition, the lifespan of the electronic component such as insulated-gate bipolar transistor (IGBT) may shorten and many faults related to the inverter especially switches can be occur. The present of VSI switches faults causing equipment failure and increased the cost of manufacturing process. Therefore, faults detection analysis is mandatory to identify the VSI switches faults. This paper presents the analysis of VSI switches faults using time-frequency distributions (TFDs) which are short times Fourier transform (STFT) and spectrogram. From time-frequency representation (TFR) obtained by using the TFDs, parameters of the faults signal are estimated such as instantaneous of average, root mean square (RMS), fundamental, Total Waveform Distortion (TWD), Total Harmonics Distortion (THD) and Total non-Harmonic Distortion (TnHD) of current signals. Then, based...
Applied Mechanics and Materials, 2015
Power quality is main issue because of the impact to electricity suppliers, equipments, manufactu... more Power quality is main issue because of the impact to electricity suppliers, equipments, manufacturers and user.To solve the power quality problem, an analysis of power quality disturbances is required to identify and rectify any failures on power system. Most of researchers apply fourier transform in power quality analysis, however the ability of fourier transform is limited to spectral information extraction that can be applied on stationary disturbances. Thus, time-frequency analysis is introduced for analyzing the power quality distubances because of the limitation of fourier transform. This paper presents the analysis of real power quality disturbances using S-transform. This time-frequency distribution (TFD) is presented to analyze power quality disturbances in time-frequency representation (TFR). From the TFR, parameters of the disturbances such as instantaneous of root mean square (RMS), fundamental RMS, total harmonic distortion (THD), total nonharmonic distortion (TnHD) and...
2014 IEEE 8th International Power Engineering and Optimization Conference (PEOCO2014), 2014
In modern power networks, the issue of power quality (PQ) is becoming very important because of t... more In modern power networks, the issue of power quality (PQ) is becoming very important because of the increasing of load which sensitive to current disturbances. This is mainly due to the increasing use of non-linear power electronic devices draws nonsinusoidal current and creating a current distortion. As a result there is increasing need for PQ to be monitored to establish the type, sources and locations of PQ disturbances, allowing remedial measures to be taken. Consequently, harmonic is one of the most concerned power quality disturbances. The detection of harmonic source is necessary for power quality strategy development. This paper introduces a new single-point measurement method to estimate the harmonic source by using phase spectrogram (PS) and frequency spectrogram (FS) based on a vector draft method. A measurement at the point of common coupling (PCC) with harmonic distortion is done by simulation via PSCAD. Then PSCAD's data are analyzed by using spectrogram in MATLAB. To be precise, voltage and current waveforms are normalized with fundamental magnitude respectively. Next, the normalized voltage and current are plotted on the vector draft to estimate the perpendicular point between the vectors. The center point of the normalized voltage is the boundary between downstream and upstream. The harmonic source can be detected base on the perpendicular point's location that fall on the particular region. The comparison between actual and power direction result have been conducted. Finally, the proposed method is similar with the actual result and more truthful than power direction method.
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Papers by Abdul Rahim Abdullah