Search Results (32)

To address the lack of robustness against illumination and blurring variations in aerial images of transmission towers, an improved image matching algorithm for aerial images is proposed. The proposed algorithm consists of two main components: an enhanced AKAZE algorithm and an improved three-stage feature matching strategy, which are used for feature point detection and feature matching, respectively. First, the improved AKAZE enhances image contrast using Contrast-Limited Adaptive Histogram Equalization (CLAHE), which highlights target features and improves robustness against environmental interference. Subsequently, the original AKAZE algorithm is employed to detect feature points and construct binary descriptors. Building upon this, an improved three-stage feature matching strategy is proposed to estimate the geometric transformation between image pairs. Specifically, the strategy begins with initial feature matching using the nearest neighbor ratio (NNR) method, followed by outlier rejection via the Grid-based Motion Statistics (GMS) algorithm. Finally, an improved Random Sample Consensus (RANSAC) algorithm computes the transformation matrix, further enhancing matching efficiency. Experimental results demonstrate that the proposed method exceeds the original AKAZE algorithm’s matching accuracy by 4∼15% on different image sets while achieving faster matching speeds. Under real-world conditions with UAV-captured aerial images of transmission towers, the proposed algorithm achieves over 95% matching accuracy, which is higher than other algorithms. Our proposed algorithm enables fast and accurate matching of transmission tower aerial images. Full article

Development challenges in the domain of superconducting magnets are concentrated on technical problems in the current literature. Organizational, domain-specific challenges are often seen as secondary but must be considered with new holistic development approaches like Model-Based Systems Engineering (MBSE) becoming more popular. This work quantifies the domain challenges and gives the foundation to derive success criteria for design support in the future. A systematic literature review has been conducted to identify the overall domain challenges, and extensive interviews in the CERN technology department have been carried out to identify the development challenges on a practical level. Problems in knowledge management have been identified as a major challenge in the development process and the general literature. The paper concludes by picking up the most important challenges from the interviews and literature and puts them into the context of the authors’ knowledge of electrical magnet design. Full article

A comprehensive model for micro-powered piezoelectric generator (PG), analysis of operation, and control of voltage doubler joule thief (VDJT) circuit to find the piezoelectric devices (PD’s) optimum functioning points are discussed in the present article. The proposed model demonstrates the power dependence of the PG on mechanical excitation, frequency, and acceleration, as well as outlines the load behaviour for optimal operation. The proposed VDJT circuit integrates the combination of voltage doubler (VD) and joule thief circuit, whereas the VD circuit works in Stage 1 for AC (alternating current)–DC (direct current) conversion, while a joule thief circuit works in Stage 2 for DC–DC conversion. The proposed circuit functions as an efficient power converter, which converts power from AC–DC and boosts the voltage from low to high without employing any additional electronic components and generating duty cycles. The electrical nature of the input (i.e., PD) of a VDJT circuit is in perfect arrangement with the investigated optimisation needs when using the proposed control circuit. The effectiveness of the proposed VDJT circuit is examined in terms of both simulation and experiment, and the results are presented. The proposed circuit’s performance was validated with available results of power electronics interfaces in the literature. The proposed circuit’s flexibility and controllability can be used for various applications, including mobile battery charging and power harvesting. Full article

DC–DC converters are used in many power electronics applications, such as switching power supply design, photovoltaic, power management systems, and electric and hybrid vehicles. Traditionally, DC–DC converters are linearly modeled using a typical operating point for their control design. Some recent works use nonlinear models for DC–DC converters, due to the inherent nonlinearity of the switching process. In this sense, a standout modeling technique is the Takagi–Sugeno fuzzy exact method due to its ability to represent nonlinear systems over the entire operating range. It is more faithful to system behavior modeling, and allows a nonlinear closed-loop control design. The use of nonlinear models allows the testing of controllers obtained by linear methods to operate outside their linearization point, corroborating with robust controllers for specific applications. This work aims to perform the exact fuzzy Takagi–Sugeno modeling of a buck–boost converter with non-ideal components, and to design a discrete proportional–integral–derivative (PID) controller from the pole cancellation technique, obtained linearly, to test the controller at different operating points. The PID control ensured a satisfactory result compared with the stationary value of the different operating points, but it did not reach the desired transient response. Since the proposed model closely represents the operation of the buck–boost converter by considering the components’ non-idealities, other control techniques that consider the system’s nonlinearities can be applied and optimized later. Full article

In this paper, four machine learning algorithms are examined regarding their effectiveness in dealing with a complete lack of sensor drift values for a crucial parameter for ship performance evaluation, such as a ship’s speed through water (STW). A basic Linear Regression algorithm, a more sophisticated ensemble model (Random Forest) and two modern Recurrent Neural Networks i.e., Long Short-Term Memory (LSTM) and Neural Basis Expansion Analysis for Time Series (N-Beats) are evaluated. A computational algorithm written in python language with the use of the Darts library was developed for this scope. The results regarding the selected parameter (STW) are provided on a real- or near-to-real-time basis. The algorithms were able to estimate the speed through water in a progressive manner, with no initial values needed, making it possible to replace the complete missingness of the label data. A physical model developed with the simulation platform of Siemens Simcenter Amesim is used to calculate the ship STW under the real operating conditions of a banker ship type during a period of six months. These theoretically obtained values are used as reference values (“ground-truth” values) to evaluate the performance of each of the four machine learning algorithms examined. Full article

The paper describes the design and implementation of a cutting fluid monitoring system, as well as the design and development of an algorithm to increase the life of the cutting fluid in the machine tool reservoir. Cutting fluids are the most common type of coolant in machining. During its use, it becomes contaminated and gradually degrades until it needs to be replaced with fresh fluid. To increase its effective service life, its parameters should be monitored at regular intervals, and corrective measures such as topping up the fluid quantity and adding inhibitors and additives should be taken if necessary. For this purpose, a conceptual design of a monitoring device was developed, and a prototype device was subsequently manufactured. The device is designed as a floating probe in the storage tank. Therefore, its shape had to be designed to accommodate multiple sensors, batteries, and electronic components while remaining floating and watertight. The designed prototype was made by additive manufacturing and placed in a cutting fluid while being measured at regular intervals. In the event of non-compliant parameters, the algorithm generated corrective actions, and the machine operator could take the required steps to significantly increase the lifetime of the cutting fluid. Full article

In the design process, design changes are unavoidable due to the need to meet customers’ requirements and support future change through technology development. Although components are supposed to be renewed within existing designs, these changes can propagate into other parts due to their interfaces. Propagation makes it difficult for a designer to identify these changes. This study aimed to introduce the integration matrix (I-DSM), an approach to the design of mechatronic products that involves determining changes in existing products with an axiomatic design. Reverse zigzagging was used to break down the entire product to its lowest level. A design matrix (DM) was constructed and then transformed into a design structure matrix (DSM). The I-DSM consists of three layers: information technology, electrical technology, and mechanical technology. The breadth-first search (BFS) method was employed to ascertain the change propagation path in order to consider it. After this, the changing workload was analyzed, and the decision-making process was used to determine the best possible option. Finally, an automatic guided vehicle was used in a case study to demonstrate the use of this methodology by showing how changes in a product can affect it and how a designer can prioritize activities. Full article

The development of an effective sensor system that can detect carcinogenic hydrazine is of prime scientific interest for the protection of human health and the environment. In the present study, MoS₂ quantum dots (QDs) with an average diameter of ~5 nm were synthesized using a facile one-step, bottom-up hydrothermal method using cysteine as reducing as well as capping agents. The presence of cysteine was evaluated by FTIR spectroscopy. The synthesized MoS₂ QDs were applied to modify the conventional glassy carbon electrode (GCE) in order to detect hydrazine electrochemically in neutral pH conditions. In the cyclic voltammetry (CV) study, the MoS₂ QDs-modified electrode revealed much better catalytic activities for hydrazine electro-oxidation compared to the bare GCE surface. The smaller size of the QDs with high surface area and the presence of carboxylic acid containing cysteine on the surface of the QDs enhanced the adsorption as well as the electrocatalytic activity. The amperometric response of MoS₂-QD-modified GCE unveiled excellent electrocatalytic sensing properties towards neurotoxic hydrazine with a very high sensitivity of 990 μAmM⁻¹cm⁻² (R² = 0.998), low LOD of 34.8 μM, and a broad linear range. Moreover, this high-sensitive, binder and conducting filler-free MoS₂-QD-based sensing system is very promising in agile amperometric detection of neurotoxic hydrazine for environmental monitoring in industrial sectors. Full article

In this paper, we propose a metamaterial (MTM)-based low-profile wideband antenna and its array using a substrate integrated cavity (SIC) feed structure for 5G wireless cellular networks. The proposed wideband antenna consists of two sets of square mushroom-like arrays; a semi-ground plane and a microstrip line-fed bow-tie radiator. Due to the unique in-phase reflection characteristic of the mushroom-like metamaterial, the bow-tie antenna wideband performance is maintained while the distance between the bow-tie radiator and the metamaterial-based semi-ground is considerably reduced to 0.014λ₀ (λ₀ is the operating wavelength at 5 GHz in free space), thereby satisfying the compact size requirement desirable in many wireless communication systems. The in-phase reflection of the mushroom unit cell is applied to analyze and explain the wideband performance of the presented antenna. The proposed dielectric-filled (${\epsilon }_r=3.55$) MTM-based wideband antenna element has an overall size of 1.0λ₀ × 0.8λ₀ × 0.054λ₀ and attains a measured ($\left|{\mathrm{S}}_{11}\right|<-10\mathrm{dB}$) bandwidth of 31.3%. Subsequently, an SIC feed structure is employed to form an array antenna, and a measured ($\left|{\mathrm{S}}_{11}\right|<-10\mathrm{dB}$) bandwidth of about 17% is obtained. Across the operating bandwidth, which partly covers the 5G wireless communication in the sub-6 GHz band and 5-GHz WLAN, the antenna array achieved an average gain of 6.6 dBi and a radiation efficiency greater than 73%. Full article

This paper describes a vector-controlled Permanent Magnet Synchronous Motor (PMSM) drive system with the current sensor fault detection mechanism. In general, the control structure is based on the well-known Field Oriented Control (FOC) algorithm. The structure is equipped with an additional algorithm for current sensor fault detection based on a neural network. The presented control structure is able to detect typical current sensor faults, such as lack of signal, intermittent signal, variable gain and signal noise. The application of the NN detector guarantees a faster detection of the sensor fault than classical detectors based on algorithmic methods or logical systems. This work focuses on presenting the methodology of designing detectors and their analysis, based solely on simulation analysis. The simulation results, conducted in the Matlab/Simulink environment, are presented for the above-mentioned faults in phase A and phase B for different speed conditions. Full article

As additively manufactured radio frequency (RF) design expands towards higher frequencies, performance becomes ever more sensitive to print-induced dimensional variations. These slight deviations from design dimensions typically skew RF performance, resulting in low yields or poor device performance. In order to overcome this limitation, RF design paradigms must be developed for non-uniform process and material-specific variations. Therefore, a new generalized approach is developed to explore variation-tolerant designs for printed RF structures. This method evaluates the feature fidelity and S11 performance of micro-dispensed, X-band (8–12 GHz) patch antennas by evaluating the standard deviation in as-printed features, surface roughness, and thickness. It was found that the traditional designs based on optimal impedance matching values did not result in the most robust performance over multiple printing sessions. Rather, performance bounds determined by print deviation could be utilized to improve large-batch S11 results by up to 7 dB. This work demonstrates that establishing the average standard deviation of printed dimensions in any RF printing system and following the formulated design procedure could greatly improve performance over large datasets. As such, the method defined here can be applied to improve large-scale, printed RF yields and enable predictive performance metrics for any given printing method. Full article

Technology has been contributing significantly to the development of assistive devices for disabled persons (DPs). Many of these devices aim to assist people who are blind or visually impaired, providing them with friendlier ways to interact with their surroundings (obstacles, objects, and navigation). However, the high cost of these devices makes it difficult for DPs to purchase them. The development of an assistive device kit to be used by the visually impaired in controlled environments (indoor) or urban spaces (outdoor) is presented in this work with a didactic and detailed approach. This low-cost kit (USD 50 per device) consists of a Smart Cane, Smart Cap, and Smart Glove. The methodology addressed aims to support and encourage the reproduction, customization, and manufacture of new assistive devices with low cost and wide applicability. The devices are functional, benefit usability, and, due to the characteristics of the project and the materials used in their construction, do not impact the ergonomics of the visually impaired or disabled person who may use these devices. The devices that integrate the assistive kit can be used independently or combined. In addition to having detection, fall-control, navigation, and real-time tracking functions, they are independent of additional local infrastructure for their use. Full article

A power generating system should be able to generate and feed quality power to the loads which are connected to it. This paper suggests a very efficient controlling technique, supported by an effective optimization method, for the control of voltage and frequency of the electrical output of an isolated wind power harnessing unit. The wind power unit is modelled using MATLAB/SIMULINK. The Leaky least mean square algorithm with a step size is used by the proposed controller. The Least Mean Square (LMS) algorithm is of adaptive type, which works on the online modification of the weights. LMS algorithm tunes the filter coefficients such that the mean square value of the error is the least. This avoids the use of a low pass filter to clean the voltage and current signals which makes the algorithm simpler. An adaptive algorithm which is generally used in signal processing is applied in power system applications and the process is further simplified by using optimization techniques. That makes the proposed method very unique. Normalized LMS algorithm suffers from drift problem. The Leaky factor is included to solve the drift in the parameters which is considered as a disadvantage in the normalized LMS algorithm. The selection of suitable values of leaky factor and the step size will help in improving the speed of convergence, reducing the steady-state error and improving the stability of the system. In this study, the leaky factor, step size and controller gains are optimized by using optimization techniques. The optimization has made the process of controller tuning very easy, which otherwise was carried out by the trial-and-error method. Different techniques were used for the optimization and on result comparison, the Antlion algorithm is found to be the most effective. The controller efficiency is tested for loads that are linear and nonlinear and for varying wind speeds. It is found that the controller is very efficient in maintaining the system parameters under normal and faulty conditions. The simulated results are validated experimentally by using dSpace 1104. The laboratory results further confirm the efficiency of the proposed controller. Full article

Electricity production from ocean waves with different solutions is a topic of major research interest. Many of such designs are based on linear generators that inherently introduce end forces. In this paper, detent force using Maxwell Stress Tensor and induced voltage is initially investigated for two different winding patterns for a generator topology with buried magnets in a finite element software. Two ways of overcoming the end forces are further examined: the first method reduces the magnetic flux variations of the translator between stator and air. The second method aims at countering the end forces at both ends for full active stator area. A comparison is then made between buried and surface-mounted topologies for the second end effect compensation method. Both no-load and load conditions are investigated in the comparison. The end effect compensation shows promising results for both topologies. Some clear similarities of the extended stator used to counter the end forces are also apparent, where the stator extensions completely cover the outer poles of both topologies. The results also indicate a longer full active stator area for the buried topology for the same pole-pitch and stroke length, resulting in a higher average voltage for partial stator overlap. Full article