This paper focuses the use of ferrite rods to miniaturize the receivers used for inductive wireless power transfer. The aim of this work is to propose an implanted solenoid coil to wirelessly power capsules using inductive coupling. The diameter and thickness of the flexible transmitter coils are 42.2 mm and 1.2 mm, respectively. The diameter of the miniaturized RX is 1.5 mm and 10 mm-length, which is appropriate for integration within current commercially available capsules. In this work, the demagnetizing factors of a ferrite-core receiver are considered. At c = 26 mm, the power received is 14 W, which corresponds to a power transfer efficiency of 60 %. Nevertheless, the receiver was still able to draw a power of 6 W at 89% efficiency at a height of 10 mm, and 6 W at 13% efficiency at 50 mm. Considering the above, we have chosen to operate the WPT link for this work at 0.125 MHz. The proposed system represents a practical proposition for WPT in capsule endoscopy. The results indicate that it shows better performance in power transfer efficiency and power received, which is in good agreement with the experimental and simulation analysis.

Misalignment is among the most frequent mechanical faults in rotating electrical machines, often resulting in partial or complete motor failure over time. To tackle this issue, the present study proposes an innovative methodology for diagnosing misalignment faults in rotating electrical machines. The method integrates the dual-tree complex wavelet transform with a refined composite multiscale fluctuation dispersion entropy algorithm (DTCWT-RCMFDE) for feature extraction, combined with the least-squares support vector machines algorithm (LSSVM) for fault classification. Initially, the DTCWT is employed to decompose the torque signal into multiple sub-bands using range entropy (RE). Subsequently, the RCMFDE is calculated for each sub-band to construct discriminative fault feature vectors. These vectors are then used to train and test the LSSVM classifier to identify different types of misalignment faults. The proposed method was validated using experimental data, and the results demonstrate its superior diagnostic performance. Compared to existing approaches, the DTCWT-RCMFDE-LSSVM model achieved the highest classification accuracy of 98.33%, outperforming other methods such as MSE-SVM (94.1%), DTCWT-EE-PSO-SVM (96%), Multi-features-t-SNE-LSSVM (96.25%) and AR model coefficients-mRMR-SOM neural network (97.22%). These findings confirm the method’s high precision in detecting both parallel and angular misalignments. This research holds significant potential for industrial applications in sectors reliant on rotating machinery such as power generation, petrochemical, nuclear, and manufacturing where early and accurate fault detection is essential to minimize downtime and enhance operational reliability.

Nowadays, improvement of power transfer efficiency is an essential way to increase the performance of a wireless power transfer system (WPT). Coil shapes have played a profound role in the performance of the WPT system, especially with the energy transmission and coupling coefficient. Planar spiral coils can provide a better energy transmission over various separations between the transmitter and receiver coils. Achieving optimum coil geometry, which maximizes the transfer quality factor of WPT system, requires a parametric study and optimization. The proposal to use a parametric study and optimization suggests analyzing the behavior of a system by varying its parameters and finding the optimal configuration based on defined criteria. A direct search method called the generalized pattern search algorithm (GPS) was used to maximize the efficiency of the WPT. A GPS algorithm was used to optimize the coil, according to the developed objective function. The GPS algorithm finds better results in a shorter computation time compared with the genetic algorithm.

Our investigation explores the complex interplay between electromagnetic field and heat transfer during the fusion process of pure gold within an induction crucible furnace through a 2D-axisymmetric model. By constructing this model, we analyze the critical warm-up phase-a period marked by substantial power requirements and extended duration. This research seeks to illuminate how various geometrical and physical parameters influence the distribution of physical fields throughout the transient heating interval. Of particular interest is the path to achieving optimal melting conditions, given the intricate coupling between electromagnetic and thermal phenomena, both of which exhibit significant nonlinear characteristics. To address these challenges, we developed a computational framework based on finite volume discretization to numerically solve the governing equations of electromagnetic and heat conduction.

Toroidal transformers are designed using a circular core instead of the traditional laminated rectangular core, which reduces inductance losses and increases efficiency. The primary goal of this study is to understand the cooling mechanisms involved in electrical transformers, which are critical components in power systems. Steady electromagnetic, fluid flow and temperature equations are simultaneously solved (direct method) using the finite elements method FEM of a shielded toroidal transformer. The paper focuses on creating a direct-coupled model (DCM) to understand the processes involved in electrical transformers cooling, using Magneto-AeroDynamic (MAD) models. The nonlinear models developed will be implemented and validated in this parametric study for different inlet velocities and the number of outlet. Transformers generate heat during operation, and it’s important to control the temperature to prevent overheating and ensure reliable operation.

PurposeBearings play a critical role in the reliable operation of induction machines, and their failure can lead to significant operational challenges and downtime. Detecting and diagnosing these defects is imperative to ensure the longevity of induction machines and preventing costly downtime. The purpose of this paper is to develop a novel approach for diagnosis of bearing faults in induction machine.Design/methodology/approachTo identify the different fault states of the bearing with accurately and efficiently in this paper, the original bearing vibration signal is first decomposed into several intrinsic mode functions (IMFs) using variational mode decomposition (VMD). The IMFs that contain more noise information are selected using the Pearson correlation coefficient. Subsequently, discrete wavelet transform (DWT) is used to filter the noisy IMFs. Second, the composite multiscale weighted permutation entropy (CMWPE) of each component is calculated to form the features vector. Finally, the features vector is reduced using the locality-sensitive discriminant analysis algorithm, to be fed into the support vector machine model for training and classification.FindingsThe obtained results showed the ability of the VMD_DWT algorithm to reduce the noise of raw vibration signals. It also demonstrated that the proposed method can effectively extract different fault features from vibration signals.Originality/valueThis study suggested a new VMD_DWT method to reduce the noise of the bearing vibration signal. The proposed approach for bearing fault diagnosis of induction machine based on VMD-DWT and CMWPE is highly effective. Its effectiveness has been verified using experimental data.

The bearing fault diagnosis plays an important role to reduce catastrophic failures and ensure the continuity of running machines to avoid heavy economic loss. The vibration signals of rolling bearings are often nonlinear and nonstationary; it is difficult to extract sensitive features and diagnose faults by traditional signal processing methods. To solve this problem, a novel intelligent fault-diagnosis approach based on whale optimization algorithm grey wolf optimization-variational mode decomposition (WOAGWO-VMD) algorithm and the marine predators algorithm optimization-least squares support vector machine (MPA-LSSVM) is proposed in this paper. Firstly, hybrid algorithm WOAGWO is used to optimize the parameters of VMD and obtain the optimal combination (K; α). Then, the optimized VMD algorithm is utilized to decompose the vibration signal of the rolling bearing into several intrinsic mode functions, and a new sensitive indicator is created to select the components containing the most information. For these components, the dispersion entropy feature, permutation entropy feature, and singular value feature are extracted to form the multi-feature vector. Finally, the feature vectors obtained are input to the MPA-LSSVM for diagnosis and identification. The validity and strength of the proposed method is verified by experimental data under different bearing conditions. The results have shown that the proposed method can extract the fault feature information of 16 bearing signals of different fault types effectively and identify them accurately.

In this paper, we presents the applications and results obtained by a direct resolution of the model MHD coupled with the Comsol Multiphysics software for the oil cooling of a high voltage transformer and another cured transformer (toric core) fed in low voltage cooled by forced air, on which our numerical models will be implemented and validated.

Eddy current (EC) sensors are used for non-destructive testing since they are able to probe conductive materials. Despite being a conventional technique for defect detection and localization, the main weakness of this technique is that defect characterization, of the exact determination of the shape and dimension, is still a question to be answered. In this work, we demonstrate the capability of small crack sizing using signals acquired from an EC sensor. We report our effort to develop a systematic approach to estimate the size of rectangular and thin defects (length and depth) in a conductive plate. The achieved approach by the novel combination of a finite element method (FEM) with a statistical learning method is called least square support vector machines (LS-SVM). First, we use the FEM to design the forward problem. Next, an algorithm is used to find an adaptive database. Finally, the LS-SVM is used to solve the inverse problems, creating polynomial functions able to approximate the correlation between the crack dimension and the signal picked up from the EC sensor. Several methods are used to find the parameters of the LS-SVM. In this study, the particle swarm optimization (PSO) and genetic algorithm (GA) are proposed for tuning the LS-SVM. The results of the design and the inversions were compared to both simulated and experimental data, with accuracy experimentally verified. These suggested results prove the applicability of the presented approach.

A 3-D model of a microwave plasma (mwp)-enhanced chemical vapor deposition (PECVD) reactor at 2.45 GHz in argon at low pressure describing self-consistently, the coupling of the microwave energy into the plasma is presented. The characteristics of the discharge are simulated using a fluid plasma model which solves the electron and ion continuity equations, electron energy balance equation, and the Poisson's equation by finite element method, using COMSOL Multiphysics software. The physical behavior of the microwave PECVD discharge, such as plasma density, electron temperature, electric field and plasma potential, are simulated and analyzed. The chemical reactions considered in this paper are: elastic, superelastic, excitation, ionization, penning ionization and metastable quenching processes, involving electrons, ions (Ar + ), neutral atoms (Ar), and excited metastable argon atoms (Ar*). The plasma characterization results are studied for a gas temperature of 300 K, a gas pressure of 100 mtorr and a microwave power of 600 W. The effect of varying gas pressure from 50 to 200 mTorr has been studied. The obtained results turn out to be in agreement with previous measurements and show that this kind of model can lead to a better understanding of the physical processes occurring in this kind of microwave reactor and thus allow optimization of this device.

This work is interested by modeling and simulation of an association Inverter-asynchronous machine. the modeling of the asynchronous machine made by a study, by using the simplifying assumptions. the order of the converter (inverter) is based on the method - Pulse Width of Modulation (PWM)-. Which brought better a quality of control, dynamics and precision.

A numerical model of radio-frequency (RF) discharge is developed to simulate the electromagnetic field, fluid flow and heat transfer in an inductively coupled plasma torch working at low pressure for argon plasma. This model will be of fundamental importance in the design of the plasma magnetic control system. Electric and magnetic fields inside the discharge chamber are evaluated by solving a magnetic vector potential equation. To start with, the equations of the ideal magnetohydrodynamics theory will be presented describing the basic behaviour of magnetically confined plasma and equations are discretized with finite element method in cylindrical coordinates. The discharge chamber is assumed to be axially symmetric and the plasma is treated as a compressible gas. Plasma generation due to ionization is added to the continuity equation. Magnetic vector potential equation is solved for the electromagnetic fields. A strong dependence of the plasma properties on the discharge conditions and the gas temperature is obtained.

Stator turn faults in permanent magnet synchronous motors (PMSMs) are more dangerous than those in induction motors (IMs) because of the presence of spinning rotor magnets that can be turned off at will.Condition monitoring and fault detection and diagnosis of the PMSM have been receiving a growing amount of attention among scientists and engineers in the past few years.The aim of this study is to propose a new detection technique of stator winding faults in a three-phase PMSM.This technique is based on the image analysis and recognition of the stator current Concordia patterns, and will allow the identification of turn faults in the stator winding as well as its correspondent fault index severity.A test bench of a vector controlled PMSM motor behaviors under short circuited turn in two phases stator windings has been built.Some experimental results of the phase to phase short circuits have been performed for diagnosis purpose.

Our study is about the modeling of tridimensional plasma enhanced chemical vapor deposition (PECVD) reactors at 2.45 GHz frequency operating in Argon, to understand the distribution of its electromagnetic field in tow cases in presence of plasma and in absence and the effect of the plasma on the electromagnetic distribution, the flow of the gas/plasma system, and the plasma-to-gas heat transfer. The aim of the modeling is to describe the gas/plasma system in terms of its field, velocity and energy, by coupling two calculation modules: electromagnetic, which solves Maxwell's equations considering the permittivity of the different media, hydrodynamic, which solves the Navier-Stokes' equations for the gas/plasma system by finite element method. The effect of micro wave excitation, frequency and gas flow is considerate in our study.

The paper aims to clarify the modelling results concerning the heat transfer and fluid flow in a radio-frequency plasma torch with argon at atmospheric pressure. Fluid numerical simulation requires the coupling of magnetohydrodynamics (MHD) and thermal phenomena. This model combines Navier-Stokes equations with the Maxwell's equations for compressible fluid and electromagnetic phenomena successively. A numerical formulation based on the finite element method is used. In this study, fluid flow and temperature equations are simultaneously solved (direct method, instead of using the indirect method) using a finite elements method (FEM) for optically thin argon plasmas under the assumptions of local thermodynamic equilibrium (LTE) and laminar flow. Appropriate boundary conditions are given, and nonlinear parameters such as the thermal and electrical conductivity of the gas and input power used in the simulation are detailed. We have found that the source of power is located on the torch wall in this type of inductive discharge. The center can be heated by conduction and convection via electromagnetic phenomena (power loss and Lorentz force). (C) 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Magnetohydrodynamics (MHD) describes the physical behavior of inductively coupled plasma (ICP). The goal of this paper is to provide a physical understanding of a process ICP torch using a resistive MHD model. This includes a basic description and derivation of the fluid model. Inductive plasma is treated as a continuous, conducting fluid that satisfies the classical laws of motion and thermodynamics. This model combines fluid equations, similar to those used in fluid dynamics, with Maxwell's equations. Steady fluid flow and temperature equations are simultaneously solved (direct method) using a finite elements method (FEM). The electromagnetic field equations are formulated in terms of potential vector with applied voltage source, so this model is physically more consistent, a more accurate and a faster simulation. The governing resistive MHD equations for an inductive plasma flow under local thermodynamic equilibrium (LTE) and laminar flow are presented, with appropriate boundary conditions. The model enabled to obtain the electromagnetic fields, temperature and flow velocity distributions also allows the determination of the electric parameters such as impedance of the plasma torch, total power, eddy losses, etc.

This article describes the three dimensional electromagnetic modeling of a microwave (2.45 GHz) plasma device, based on an axial injection torch (AIT). The model solves Maxwell's equations by the finite integration technique (FIT). We are interested in obtaining the optimal position of the short circuit in order to obtain the best percentage of coupling at 2.45 GHz. and understanding the influence of various geometrical parameters on the physical distribution of the electromagnetic field and on the power transfer within the structure.

In this paper, a new 2-D nonlinear direct-coupled model for the simulation of inductively coupled plasma torches working at atmospheric pressure is presented. Steady fluid flow and temperature equations are simultaneously solved (direct method) using a finite-element formulation for optically thin argon plasmas under the assumptions of local thermodynamic equilibrium and laminar flow. The electromagnetic field equations are formulated in terms of potential vector with applied voltage source.

This paper describes electromagnetic (EM) phenomena in plasma torches systems with and without plasma, at atmospheric pressure. Steady fluid flow and temperature equations are simultaneously solved (direct method) using a finite elements formulation for optically thin argon plasmas under the assumptions of local thermodynamic equilibrium (LTE) and laminar flow. The electromagnetic field equations are formulated in terms of potential vector. The governing magnetohydrodynamics (MHD) equations for an inductive plasma flow under LTE are presented, appropriate boundary conditions are given, and nonlinear parameters, such as the thermal and electrical conductivity of the gas and input power used in the simulation, are detailed.