Nurul Aini Bani

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals.

Design of Solar Powered Charging Backpack

Efficiency, reliability, high power quality and continuous operation are important aspects in electric vehicle attraction system. Therefore, quick fault detection, isolation and enhanced fault-tolerant control for open-switches faults in inverter driving systems become more and more required in this filed. However, fault detection and localization algorithms have been known to have many performance limitations due to speed variations such as wrong decision making of fault occurrence. Those weaknesses are investigated and solved in this paper using currents magnitudes fault indices, current direct component fault indices and a decision system. A simulation model and experimental setup are utilized to validate the proposed concept. Many simulation and experimental results are carried out to show the effectiveness of the proposed fault detection approach.The inverter with critical loads should be able to provide critical loads with a stable and seamless voltage during control mode change as well as clearing time. The indirect current control has been proposed for providing stable voltage with critical load during clearing time and seamless control mode transfer of inverters. However, the islanding detection is difficult since with the indirect current control the magnitude and frequency of voltage do not change when the islanding occurs. The conventional anti-islanding method based on the magnitude and frequency of voltage variation cannot apply to the indirect current control. This paper proposes an islanding detection method for the indirect current control. The proposed islanding detection method can detect the islanding using reactive power perturbation and observation when the frequency and magnitude of voltage don’t vary during clearing time. In order to verify the proposed anti-islanding method, the experimental results of a 600W three-phase inverter are provided.

Critical Design Factors on Performance of Car Jack Lifting Operations

Applied Computing Technology (ACT), Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, 86400 Johor, Malaysia. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, 86400 Johor, Malaysia. Department of Management Information Systems, College of Commerce and Business Administrations, Dhofar University, Salalah, Oman.

Effect of diffuse radiation on the performance of a rotationally asymmetrical optical concentrator

This paper evaluates the performance of a recently patented rotationally asymmetrical dielectric totally internally reflective concentrator (RADTIRC) under diffuse radiation. The RADTIRC has a geometrical concentration gain of 4.969 and two half acceptance angles of ± 30° and ± 40° along the x-axis and z-axis respectively. Simulation and experimental work have been carried out to determine the optical concentration gain under diffuse radiation. It was found that the RADTIRC has an optical concentration gain of 1.94 under diffuse irradiance. The experimental results for the single concentrator showed an optoelectronic gain of 2.13, giving a difference of 9.8% due to factors such as the presence of direct radiation during experiments, the increase in diffuse radiation due to the reflection from surrounded buildings as well as from the ground reflection.

Recognition of body segment based on human electromagnetic radiation analysis

The human body is shown have their own radiation, which emits at certain frequencies into space on their surrounding body. This study proposes an approach for recognition of human body segments based on electromagnetic radiation of human body. Four human body segments are considered called as Upper body, Torso, Arm and Lower Body. A-nearest neighbor (KNN) classifier is employed as pattern recognition technique to classify the human body segments and the performance of the classifier is evaluated using receiving operating characteristic (ROC). The results show that the proposed technique properly classifies the body segments with 93.75% accuracy. Experimental results recommend that the proposed technique is appropriate and capable to classify body segments using frequency analysis of human electromagnetic radiation.

EEG features extraction and k-NN classification during eyes closed

The aim of this study was to determine the number of EEG behaviours existed during eyes closed. The EEG signals before and after stress test were selected and computed into the EEG features known as asymmetry index (AsI). In order to determine the number EEG behaviours, the cluster centers of the EEG features were tested using subtractive clustering (SC). The maximum number of three clusters centers was identified and Fuzzy C-Means (FCM) was employed to segregate the data features into similar group. In order to test which clusters number gives highest classification, the FCM was executed separately for three clusters and two clusters. Subsequently, the k-Nearest Neighbour (k-NN) was used to classify the three clusters and two clusters and the classification rates were compared. The classification results showed that the number of two clusters give higher classification rate which was 100%.

Modelling the Effect of Applied Voltage and Frequency on Electroluminescence in Polymeric Material

N. A. Bani, Z. Abdul-Malek, F. Muhammad-Sukki, A. Abubakar Mas’ud, M. N. Muhtazaruddin, K Kamardin, J. J. Jamian, H. Ahmad Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia Institute of High Voltage and High Current (IVAT), Universiti Teknologi Malaysia, Johor, Malaysia School of Engineering, Faculty of Design and Technology, Robert Gordon University, Aberdeen, United Kingdom Faculty of Engineering, Multimedia University, Persiaran Multimedia, Cyberjaya, Selangor, Malaysia Department of Electrical and Electronic Engineering Technology, Jubail Industrial College, Saudi Arabia Advanced Informatics School, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor, Malaysia Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Malaysia

Statistical Analysis of Breakdown Voltages in Virgin and Aged LDPE Using Johnson SB and Weibull Distribution

Polymeric material such as low density polyethylene (LDPE) has been used for decades as insulating material. Any polymeric material will experience degradation after prolonged application of high electrical stresses. Deeper understanding of the long term electrical degradation of the insulating material is necessary to predict the life of high voltage cable. Electroluminescence method (EL) is used to detect the breakdown voltages of thin film LDPE. This method utilizes a Peltier cooled electron multiplying charge coupled device (EMCCD) camera to detect the breakdown of the sample. Statistical distribution of the AC breakdown voltages of 100μm virgin and aged LDPE has been analysed. Comparison for the best fitted distribution was made for Weibull distribution and Johnson SB distribution using Anderson-Darling (A2) goodness-of-fit and Kolmogorov-Smirnov (D) goodness-of-fit (GOF). Johnson SB is rarely used in high voltage engineering application. The probability density function (PDF) and the cumulative density function (CDF) for both distributions are defined in this article. The statistical parameters used are estimated based on Maximum Likelihood Estimation (MLE) for both distributions. Based on the statistical analysis, it is observed that Johnson SB provide better fitting than Weibull distribution with lower fitting error and that 3-parameter Weibull is much better fitting than 2-parameter Weibull distribution for most cases. It is also found that the median breakdown voltage of LDPE samples decreases with increasing aging temperature.

Characteristics of electroluminescence phenomenon in virgin and thermally aged LDPE.

High voltage cable requires a good insulating material such as low density polyethylene (LDPE) to be able to operate efficiently in high voltage stresses and high temperature environment. However, any polymeric material will experience degradation after prolonged application of high electrical stresses or other extreme conditions. The continuous degradation will shorten the life of a cable therefore further understanding on the behaviour of the aged high voltage cable needs to be undertaken. This may be observed through electroluminescence (EL) measurement. EL occurs when a solid-state material is subjected to a high electrical field stress and associated with the generation of charge carriers within the polymeric material and that these charges can be produced by injection, de-trapping and field-dissociation at the metal-polymer interface. The behaviour of EL emission can be affected by applied field, applied frequency, ageing time, ageing temperature and types of materials, among others. This paper focuses on the measurement of EL emission of additive-free LDPE thermally aged at different temperature subjected to varying electric stresses at 50Hz. It can be observed that EL emission increases as voltage applied is increased. However, EL emission decreases as ageing temperature is increased for varying applied voltage.

Statistical error tolerances of partial discharge recognition rates

This paper compares the statistical error tolerances of the single neural network (SNN) and the ensemble neural network (ENN) recognition efficiencies, when both the SNN and ENN are applied to recognize partial discharge (PD) patterns. Statistical fingerprints from the phased and amplitude resolved patterns of PDs, have been applied for training and testing the SNN and the ENN. Statistical mean and variances of the SNN and ENN recognition rates were compared and evaluated over several iterations in order to obtain an acceptable value. The results show that the ENN is generally more robust and often provides an improved recognition rate with higher mean value and lower variance when compared with the SNN. The result implies that it is possible to determine the accurate statistical error tolerances for the SNN and ENN recognition probability for correct diagnosis of PD fault.