Normalized Array Factor Research Articles

Electric Discharges Localization for Substation Fault Monitoring Using Two Elements Sensor

A substation is an important unit in the electric power system. Thus, the monitoring process must be carried out effectively to detect the operation status of the equipment, and pre-fault threat detection is necessary for safe operation. Many methods and intelligent techniques have been developed to provide a better way of fault detection. However, power authorities unwilling to adopt those techniques due to the high cost of installation and more sensors required to improve localization accuracy. Therefore, to reduce cost and increase the speed of detection, this paper presents a 2-element array antenna acted like a sensor to detect and localize the electric discharges from abnormal radiated electromagnetic activities in the substation based on the direction of arriving angle (DOA) received by the array antenna. Software implemented signal processor was used to obtain the radiation patterns for different value of DOA relative to the normalized Array Factor (AFN). This 2-element Sensor was proven to eliminate the undesired signals (such as electromagnetic signals from outside the substation) and maximize the signals in the direction of the desired signal by detecting the DOA of abnormal radiation from power apparatus (such as power transformer or circuit breaker bushings) inside the substation. It was proven that this cohesive unit was able to perform the two tasks by simultaneously eliminating or maximizing signals with very small (such as 0.0873 radians) angle difference between external radiation and radiation from apparatus inside the substation. By performing these tasks, the 2-element Sensor was promisingly able to detect and localize the abnormal electrical activities such as Electric Corona and Electric Arcs discharges that may occur in any substation based on the identified DOA from the power apparatus within the substation as a preventative approach for substation breakdown and to improve the efficiency and the performance of fault detection technique in future Substation Fault Monitoring.

DETECTION AND LOCALIZATION OF ELECTRIC DISCHARGES IN INDOOR SUBSTATION FOR FAULT MONITORING

Power Substation is the most important unit in the power system, therefore, the monitoring process must be carried out effectively to detect the operation status of the equipment, and the maintenance is necessary for safe operation. Substation faulty such as Dielectric breakdowns, originating from the insulation degradation is still a major issue in the power system (1–3). Many methods and techniques with intelligence approaches have been developed to provide a better way of fault detection in a substation. However, not many are willing to adopt those techniques by reasoning the high cost of installation and more sensors required to improve localization accuracy (4). Therefore, to reduce cost and increase the speed of detection, this paper presents a 2-element array antenna to perform as a sensor to detect and localize the electric discharges (ED) produced by abnormal radiated electromagnetic activities in substation based on the direction of arriving angle (DOA) received by elements in the array antenna. The radiation patterns obtained were then visualized using software of signal processing based on the normalized Array Factor (AFN). This sensor has shown its efficiency in eliminating the interferer signals at random DOA of and maximizing the desired signal at DOA of 45˚; the identified angle direction from the substation power apparatus. This sensor has the ability to be steered isotopically and terminate or maximize signals which differ by or 0.0873 radians of DOAs, simultaneously. Having these abilities allowed this sensor to be a cohesive unit in detecting and localizing the abnormal radiated electromagnetic activities in substation based on the identified DOA thus, make it as a promising preventive approach for substation breakdown and improve the performance in Substation Fault Monitoring.

An All-Passive Negative Feedback Network for Broadband and Wide Field-of-View Self-Steering Beam-Forming With Zero DC Power Consumption

This paper presents an all-passive negative feedback network that performs autonomous radio-frequency (RF) front-end beam-forming and dynamic beam-tracking toward the direction of the incident RF signal. The proposed feedback network consists of a passive RF signal processing network, voltage rectifiers, and voltage-controlled delay-line phased shifters, all of which are passive-only circuits. The negative feedback loop is realized by passive phase detection, phase-to-voltage conversion, and voltage-controlled phase shifting, achieving a large loop-gain and autonomous operation with zero DC power consumption. The nonlinear behavior of the loop is exploited to substantially expand the array field of view (FoV). A proof-of-concept broadband four-element all-passive self-steering beam-former at 5 GHz with a wide FoV is implemented in a standard 130 nm CMOS process. A high-quality four-element synthesized array factor is measured for the input progressive phase shift $\phi _{\mathrm {in}}$ from −180° to 180°. When the proposed negative feedback loop is enabled, the normalized array factor is −2.87/−2.8 dB at $\phi _{\mathrm {in}}= + 90^{\circ }$ /−90° with an input RF power $\text{P}_{\mathrm {in}}$ of −17 dBm/element at 5 GHz, achieving >25 dB array factor improvement over the open-loop operation. Moreover, the nonlinear feedback loop allows for significant array factor improvement even at $\phi _{\mathrm {in}} = +180^{\circ }$ /−180°. The proposed beam-former also achieves high-quality self-steering beam-forming from 4 to 5.68 GHz with 34.7% fractional bandwidth. Therefore, the proof-of-concept all-passive self-steering beam-former outperforms the state-of-the-art active designs in terms of beam-forming quality, FoV, and fractional bandwidth. To the best of the authors’ knowledge, this is the first demonstration of an all-passive negative feedback network for a broadband and wide FoV self-steering beam-forming with zero DC power consumption.

Improvement of Adaptive Smart Concentric Circular Antenna Array Based Hybrid PSOGSA Optimizer

Unlike all recent research which used Concentric Circular Antenna Array (CCAA) based on one beam-former for each single main beam, this research presents a technique to adapt smart CCAA by using only single beam-former for multi main beams based on hybrid PSOGSA. Hybrid PSOGSA is a combining technique between Particle Swarm Optimization and Gravitational Search Algorithm which is applied in the feeding of the smart CCAA to enhance its performance. Phase excitation of the array with a large number of elements is suggested for different scenarios based on hybrid PSOGSA and other algorithms such as PSO and GSA in High Altitude Platform (HAP) application. Simulation results proved that hybrid PSOGSA achieves better performance than other optimizers for excitation of the smart CCAA in all scenarios for different parameters like normalized array factor, fitness values, convergence rate, and directivity

Performance Enhancement for Adaptive Beam-Forming Application Based Hybrid PSOGSA Algorithm

Recently researchers were interested in hybrid algorithms for optimization problems for several communication systems. In this paper, a novel algorithm based on hybrid PSOGSA technique (combination of Gravitational Search Algorithm and Particle Swarm Optimization) is presented to enhance the performance analysis of beam-forming for smart antennas systems using N elements for Uniform Circular Array (UCA) geometry. Complex excitations (phases) of the array radiation pattern are optimized using hybrid PSOGSA technique for a set of simultaneously incident signals. Our results have shown tremendous improvement over the previous work was done using Uniform Linear Array (ULA) geometry and standard GSA in terms of normalized array factor and computational speed for normalized fitness values.

ADAPTIVE BEAMFORMING USING LMS ALGORITHM

The smart antennas are widely used for wireless communication, because it has a ability to increase the coverage and capacity of a communication system. Smart antenna performs two main functions such as direction of arrival estimation (DOA) and beamforming. Using beamforming algorithm . smart antenna is able to form main beam towards desired user and null in the direction of interfering signals. This paper evaluate the performance of LMS (Least Mean Square) beamforming algorithm in the form of normalized array factor (NAF) and mean square error(MSE) by varying the number of elements in the array and the placing between the sensor elements. The simulations are carried out using MATLAB.

Least Mean Square (LMS) for Smart Antenna

The demand for increased capacity in wireless communication networks has motivated recent research activities toward wireless systems that exploit the concept of smart antenna and space selectivity. Efficient utilization of limited radio frequency spectrum is only possible to use smart/adaptive antenna system. Smart antenna radiates not only narrow beam towards desired users exploiting signal processing capability but also places null towards interferers, thus optimizing the signal quality and enhancing capacity. We analysis the performance of adaptive (LMS) algorithm for smart antenna systems which is very important for smart antenna design. The SA incorporates this algorithm in coded form which calculates complex weights according to the signal environment. The performance of LMS algorithm is compared on the basis of normalized array factor and Mean Square Error (MSE) for SA systems. It is observed that an LMS algorithm is converging after 50 iteration.