Software Solutions for Antenna Design Exploration: A Comparison of Packages, Tools, Techniques, and Algorithms for Various Design Challenges

Numerous software packages exist for solving antenna design optimization problems, with many of these employing a variety of approaches, leading, in turn, to variations in optimization performance. Antenna designers, often not fully schooled in optimization, can be confused as to which algorithm in which software package should be used. A wrong choice can cause the failure of the optimization or the expending of considerable time on the computationally expensive 3D electromagnetic (EM) simulations involved. While it is true that the various algorithms, combined with the variety of complex challenges found in different real-world scenarios make a direct comparison among tools difficult, a robust attempt at such an evaluation is overdue

Accurate Antenna Gain Estimation Using the Two-Antenna Method

This paper demonstrates a simulation-assisted measurement technique to determine the gain of an antenna accurately in an open test site or anechoic chamber. The proposed technique is based on the two-antenna gain measurement method using Friis equation in far-field free-space conditions, with the actual measurement test setup modelled in CST Studio Suite for simulation. An LTE-reject UHF TV log-periodic dipole antenna is used to validate the gain measurement technique in this paper. The simulation of the two-antenna gain measurement method is used in order to estimate an appropriate minimum separation distance between the two antennas that needs to be used for actual measurements to ensure far-field free-space conditions. Determining this minimum separation distance using several simulations instead of actual measurements saves time and effort because it eliminates the need to perform measurements at various separation distances. The measured realized gain obtained using this technique provides a good agreement with the simulation and thus validates the accuracy of this technique

Efficient design optimization of high-performance MEMS based on a surrogate-assisted self-adaptive differential evolution

High-performance microelectromechanical systems (MEMS) are playing a critical role in modern engineering systems. Due to computationally expensive numerical analysis and stringent design specifications nowadays, both the optimization efficiency and quality of design solutions become challenges for available MEMS shape optimization methods. In this paper, a new method, called self-adaptive surrogate model-assisted differential evolution for MEMS optimization (ASDEMO), is presented to address these challenges. The main innovation of ASDEMO is a hybrid differential evolution mutation strategy combination and its self-adaptive adoption mechanism, which are proposed for online surrogate model-assisted MEMS optimization. The performance of ASDEMO is demonstrated by a high-performance electro-thermo-elastic micro-actuator, a high-performance corrugated membrane microactuator, and a highly multimodal mathematical benchmark problem. Comparisons with state-of-the-art methods verify the advantages of ASDEMO in terms of efficiency and optimization ability

1.62 GHz Circularly Polarized Pin-Fed Notched Circular Patch Antenna

This paper studies a circular patch antenna which is fed by using a coaxial pin, which is a suitable antenna design for applications where small size is of importance. Such applications are wearable antenna designs. The main purpose of this paper is to design an antenna with wearable capabilities and adequate radiation characteristics for satellite communications and more specifically for the Iridium satellite constellation. The goals for the radiation characteristics of the antenna are the tuning of the antenna to 1.62GHz which is the Iridium's frequency, maximum boresight gain for this frequency, as well as circular polarization

Machine Learning-assisted Antenna Design optimization: A Review and the State-of-the-art

Antenna design optimization continues to attract a lot of interest. This is mainly because traditional antenna design methodologies are exhaustive and have no guarantee of yielding successful outcomes due to the complexity of contemporary antennas in terms of topology and performance requirements. Though design automation via optimization complements conventional antenna design approaches, antenna design optimization still presents a number of challenges. The major challenges in antenna design optimization include the efficiency and optimization capability of available methods to address a broad scope of antenna design problems considering the growing stringent specifications of modern antennas. This paper presents a review of the most recent progress in antenna design optimization with a focus on methods which address the challenges of efficiency and optimization capability via machine learning techniques. The methods highlighted in this paper will likely have an impact on the future development of antennas for a multiplicity of applications

Partial Discharge Localization Based on Received Signal Strength

Partial Discharge (PD) occurs when insulation containing defects or voids is subject to high voltages. If left untreated PD can degrade insulation until, eventually, catastrophic insulation failure occurs. The detection of PD current pulses, however, can allow incipient insulation faults to be identified, located and repaired prior to plant failure. Wireless technology has paved the path for PD detection and monitoring. Software Defined Radio (SDR) is a promising technology. Signals from two PD sources are received at six outdoors locations using an SDR USRP N200 which is connected to a laptop. PD sources, thereafter, are localized based on received signal strengths

A review of techniques for RSS-based radiometric partial discharge localization

The lifespan assessment and maintenance planning of high-voltage power systems requires condition monitoring of all the operational equipment in a specific area. Electrical insulation of electrical apparatuses is prone to failure due to high electrical stresses, and thus it is a critical aspect that needs to be monitored. The ageing process of the electrical insulation in high voltage equipment may accelerate due to the occurrence of partial discharge (PD) that may in turn lead to catastrophic failures if the related defects are left untreated at an initial stage. Therefore, there is a requirement to monitor the PD levels so that an unexpected breakdown of high-voltage equipment is avoided. There are several ways of detecting PD, such as acoustic detection, optical detection, chemical detection, and radiometric detection. This paper focuses on reviewing techniques based on radiometric detection of PD, and more specifically, using received signal strength (RSS) for the localization of faults. This paper explores the advantages and disadvantages of radiometric techniques and presents an overview of a radiometric PD detection technique that uses a transistor reset integrator (TRI)-based wireless sensor network (WSN)

Low power radiometric partial discharge sensor using composite transistor-reset integrator

The measurement of partial discharge provides a means of monitoring insulation health in high-voltage equipment. Traditional partial discharge measurements require separate installation for each item of plant to physically connect sensors with specific items. Wireless measurement methods provide an attractive and scalable alternative. Existing wireless monitoring technologies which use time-difference-of-arrival of a partial discharge signal at multiple, spatially separated, sensors place high demands on power consumption and cost due to a requirement for rapid sampling. A recently proposed partial discharge monitoring system using a wireless sensor network and measuring received signal strength only, has potential cost and scalability advantages. An incoherent wireless sensor incorporating a transistor-reset integrator has been developed that reduces the measurement bandwidth of the PD events and alleviates the need for high-speed sampling. It is based on composite amplifier techniques to reduce the power requirements by a factor of approximately four without compromising precision. The accuracy of the proposed sensor is compared to that obtained using a high-speed digital sampling oscilloscope. Received energies were measured over a 10 m distance in 1 m increments and produced an error within 1 dB beyond 4 m and 3.2 dB at shorter distances, resulting in a measurement accuracy within 1 m