Soib Taib

Development of a Single Phase SPWM Microcontroller-Based Inverter

This paper presents the development of single phase sinusoidal pulse width modulation (SPWM) microcontroller-based inverter. The attractiveness of this configuration is the used of a microcontroller to generate sinusoidal pulse width modulation (SPWM) pulses. Microcontroller is able to store the required commands to generate the necessary waveforms to control the frequency of the inverter through proper design of switching pulses. The SPWM technique was used to produce pure sinusoidal wave of voltage and current output. This inverter is designed to be either for stand-alone or for grid connected from a direct supply of photovoltaic (PV) cells. In this paper SPWM switching technique is first reviewed. Subsequently control circuit and power circuit for inverter are discussed. Finally the experimental results are discussed. The 200 W designed prototype of the inverter was tested with the resistive load and found that total harmonic distortion (THD) is less than 4% for voltage and 8% for current.

A new thermographic NDT for condition monitoring of electrical components using ANN with confidence level analysis

Infrared thermography technology is one of the most effective non-destructive testing techniques for predictive faults diagnosis of electrical components. Faults in electrical system show overheating of components which is a common indicator of poor connection, overloading, load imbalance or any defect. Thermographic inspection is employed for finding such heat related problems before eventual failure of the system. However, an automatic diagnostic system based on artificial neural network reduces operating time, human efforts and also increases the reliability of system. In the present study, statistical features and artificial neural network (ANN) with confidence level analysis are utilized for inspection of electrical components and their thermal conditions are classified into two classes namely normal and overheated. All the features extracted from images do not produce good performance. Features having low performance reduce the diagnostic performance. The study reveals the performance of each feature individually for selecting the suitable feature set. In order to find the individual feature performance, each feature of thermal image was used as input for neural network and the classification of condition types were used as output target. The multilayered perceptron network using Levenberg-Marquardt training algorithm was used as classifier. The performances were determined in terms of percentage of accuracy, specificity, sensitivity, false positive and false negative. After selecting the suitable features, the study introduces the intelligent diagnosis system using suitable features as inputs of neural network. Finally, confidence percentage and confidence level were used to find out the strength of the network outputs for condition monitoring. The experimental result shows that multilayered perceptron network produced 79.4% of testing accuracy with 43.60%, 12.60%, 21.40, 9.20% and 13.40% highest, high, moderate, low and lowest confidence level respectively.

Sensorless control of a BLDC motor with back EMF detection method using DSPIC

This paper proposes a scheme for sensorless control of a brushless dc (BLDC) motor by direct back EMF detection method using dsPIC30F3010. A mathematical model of the drive system is simulated with MATLAB SIMULINK Toolbox and the reference design incorporates both hardware and software parts of the system. The simulated and experimental results from a prototype BLDC drive system are verified. Experimental waveforms of phase back EMF, current and speed obtained from a 3-phase, 120 W, 4-pole, BLDC drive system are validated with simulation results. As the terminal voltage of the motor is proportional to the phase back EMF on the floating phase, the DSP-ADC feature utilized to sense the back EMF proved the validity of sensorless control over a wide speed range.

Thermal imaging for qualitative-based measurements of thermal anomalies in electrical components

This paper proposes a method of classifying the reliability of electrical equipment by analyzing their thermal images. In order to automatically analyze the thermal image, a top-down approach of image processing is used. First the distinctive feature points of the target equipment are identified. The maximally stable extremal region (MSER) algorithm is used to detect the feature points and regions of interest. Feature descriptors for each detected point are calculated and similar features are matched together by utilizing the Euclidean distance to find similar equipment within the image. These are then grouped together before proceeding with the segmentation process. The condition of the electrical equipment is evaluated by finding their real temperature values. Classification of the thermal faults within the electrical equipment is done by using qualitative-based measurements. The results indicate that this technique produces about 60% correct classifications, which is according to the recommended standards.

Magnetizing Current, Harmonic Content and Power Factor as the Indicators of Transformer Core Saturation

Abstrac t—The paper proposes a measurement method for obtaining the parameters needed to calculate a reliable indicator of the state of transformer core saturation. The major nonlinear effects in transformer core are saturation, eddy current and hysteresis. Saturation is the predominant effect in power transformers, followed by eddy current and hysteresis effects. In saturation, a transformer core act as a source of current generating harmonics, some of which will flow directly toward the primary and secondary windings. The method is based on magnetization current, harmonic content and power factor evaluated of the transformer no-load current with high magnetic flux density subjected. The investigation is done on single phase model core type transformer. The transformer is connected to variable voltage variable frequency (VVVF) source and the investigation is done on various flux densities. The results show that the magnetization current and harmonic content increase significantly when high magnetic flux densities are injected and vice versa with power factor that decrease sharply. These phenomena can be used as the indication of transformer core saturation.

Thermal Imaging for Enhancing Inspection Reliability: Detection and Characterization

Reliable performance of an equipment or structure depends on pre-service quality and in- service degradation of the equipment or structure under operating conditions. The role of non-destructive testing (NDT) is to ensure integrity, and in turn, reliability of equipment or structure. Besides, NDT can also monitor in-service degradation and to avoid premature failure of the equipments/structures and prevent accidents as well as save human life. Up to now, NDT has been used in various fields of applications such as the inspection of

LLC resonant DC-DC converter for high voltage applications

In this paper, an LLC resonant dc-dc converter is proposed for high voltage applications. Full bridge inverter, LLC resonant tanks, high voltage transformer and full bridge rectifier are comprised in the proposed converter circuit. In operating frequency of proposing converter, output voltage regulation is achieved by narrow varying. The energy trapped in leakage inductance of the transformer and to achieve ZVS feature, LLC resonant circuit is utilized to retrieve. It also increases conversion efficiency. A high voltage transformer is used to step up AC voltage which is then refined by the rectifier. With the equivalent circuit derived by first harmonic approximation (FHA method, input-output response and DC characteristics in frequency domain are obtained. The theoretical equations of the circuit operations are studied in detail to infer. Finally, a design example is implemented out to establish the feasibility of the proposed LLC resonant converter. The simulation results on the essential switching and circuit operation are presented. The robustness of this study is verified by the simulation results of the proposed converter with 300V input and 3.5kV/0.35A output.

Design considerations of a high frequency power transformer

The approach of high frequency application seems to be very trendy In power transformer design. Especially when it is greatly efficient in reducing size, losses, cost etc. However, there is not much discussion that were made on how to design the high frequency power transformer using a proper approach, cost efficient and reliable to be implemented. So in this paper, some of those important parameters are briefly considered. The discussion is made throughout their geometries, core losses, winding losses and thermal model considerations accordingly.

Effect of DC bias on magnetization current waveforms of single phase power transformer

An investigation of magnetizing current waveforms of single phase power transformer due to DC bias injection through simulation and experimental study is present in this paper. A method base on MATLAB simulation that is capable of predicting of magnetizing current without and with DC bias is used. The experimental study is done by the DC bias current injected simultaneously with AC source to primary winding of transformer and the secondary side is open circuit. The results show that the waveforms distorted when the DC bias exist. The pulsated waveforms are pushed to half cycle in which the bias current is in the same direction as magnetizing current (unsymmetrical pulsated) and even harmonics are significant. The simulated waveforms have good agreement with the measured one.

Detecting ROIs in the thermal image of electrical installations

This paper presents a method of detecting and segmenting regions of interest (ROIs) of the thermal image of electrical installations. These regions are very important in diagnosing the thermal condition of electrical equipment. Due to the nature of thermal imaging, segmentation with the conventional approach will make inaccurate ROI detection, especially when qualitative approach is considered in evaluating the equipments condition. Therefore, we take the advantage of extracting local features to identify, locate, and match multiple repeated objects and grouping a look-like similar objects in the images. Experimental results show that the proposed method achieves better performance for detecting the target ROIs with various irregular intensity variations, dim target equipments and cluttered background. The performance of the proposed method is qualitatively and quantitatively evaluated.