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Page 28 of 939 Results 271 - 280 of 9382

Simone Mari, Andrea Credo, Giovanni Bucci, Fabrizio Ciancetta, Edoardo Fiorucci, Andrea Fioravanti
Current Measurements for Fault Diagnosis in Induction Motors

Predictive maintenance has become increasingly important in modern industry as it can prevent unplanned production interruptions and reduce maintenance costs. This is especially important for companies working with expensive and complex machinery, such as those used in manufacturing, transportation, and energy. Predictive maintenance uses sensors and data analytics to monitor equipment performance and predict when a failure or breakdown might occur. This paper presents a preliminary study on the use of absorbed currents measurement of a three-phase induction motor aimed at electrical fault diagnostics. In detail, a 4-pole high efficiency induction motor with 3kW of rated power was simulated in the Ansys Electronic Desktop environment. The simulated operation is with direct mains power supply. The motor was simulated initially at no load, then load torque values of 20%, 40%, 60%, 80% and 100% of rated value were evaluated. The currents drawn on the three phases were evaluated with a computational step of 500 µs, corresponding to a sampling rate of 2 kHz. The same simulations were subsequently repeated by reproducing five different fault conditions in the motor. Therefore, an analysis of the waveforms of the absorbed currents is provided and a diagnostic system based on their analysis is proposed.

Benjamin Wenzel, Matthias Schmidt
Magnetic stray field analysis over large areas using Hall- and magneto-optical sensors

In this paper, fast and large-area measurements using Hall sensors and magneto-optical sensors are presented, which are suitable for 100% inline testing of magnetic assemblies in industry. The advantages of the two methods are explained and illustrated using real measurement examples. We show how identically designed magnetic components can be compared easily and quickly based on their stray fields. High-resolution measurements of miniaturized magnetic structures are carried out using magnetooptical measurement technology and the results are presented.

Federico Filippi, Giorgia Fiori, Gabriele Bocchetta, Salvatore Andrea Sciuto, Andrea Scorza
A Preliminary Comparison of Three Methods for the Assessment of Pulse Wave Transit Time in an Arterial Simulator

Arterial simulators are useful tools to reproduce the Pulse Wave Velocity (PWV) behavior depending on vessel characteristics. This quantity is related to the Pulse Transit Time (PTT), i.e., the time interval required for the pulse wave to travel between two sites in a vessel. In the literature, there is a lack of comparison of PTT evaluation methods from signals acquired through arterial simulators. In the present study, three PTT estimation methods (peak-to-peak, tangent-secant and cross-correlation) have been applied to two signals simulating the pressure wave traveling in an Arterial Surrogate (AS) over time. Tests have been repeated for different imposed delays between the generated waveforms. From the obtained results, the cross-correlation method showed the lowest discrepancy values between estimated and imposed time delay

Gabriele Bocchetta, Giorgia Fiori, Federico Filippi, Pietro Ursi, Salvatore Andrea Sciuto, Andrea Scorza
First results on torque estimation by FEA and experimental analysis in a novel CSFH-based microgripper

Microgrippers (MGs) are MEMS devices that can manipulate cells and microscopic objects. In this work an approach based on both experimental and a finite element analysis is proposed with the aim of evaluating the torque exerted by the micro-actuator of a novel prototype of MG equipped with electrostatic rotary comb-drives and Conjugate Surface Flexure Hinges (CSFHs) when powered by a 0-20 V peak-topeak supply voltage. The angular displacement of the micro-actuator has been measured using an image analysis method implemented by the Authors from videos acquired by a camera on a trinocular optical microscope, while the hinge stiffness has been estimated using numerical simulations: the obtained results show that the comb-drive can apply a maximum torque of 1.4 ± 0.2 nNm.

Thomas Schliesch, Thomas Lindner
Teamwork of Simulations and Hall Sensor Measurements for the Design of Magnetic Sensor Systems

New magnetic sensor systems like stray field compensating specimen demand new challenges for the design of respective permanent magnets and sensors themselves. The collaboration of FEM simulations with 3D-Hall sensor measurements provides new insights how to build and optimize such systems. The paper shows this by the example of two stray field compensating sensors for position detection of rotating systems. The first example provides different stages of the development of a new sensor. The second one shows steps during the improvement of permanent magnets for a commercially available sensor system. Both parts also supply results about the insensitivity of those sensors against external fields up to 20mT.

M. Blagojevic, A. Dieudonne, L. Kamecki, M. E. Kiziroglou, K. Krastev, D. Marty, D. Piguet, S. Spasic, S. W. Wrightand, E. M. Yeatman
The AMPWISE Project

This paper presents an energy autonomous Wireless Sensor Network (WSN) for monitoring the structural current in aircraft structures. A hybrid inductive/hall sensing concept is introduced demonstrating 0.5 A resolution, < 2% accuracy and frequency independence, for a 5 A – 100 A Root-MeanSquare (RMS), DC-800 Hz current and frequency range, with 35 mW active power consumption. An inductive energy harvesting power supply with magnetic flux funneling, reactance compensation and supercapacitor storage is demonstrated to provide 0.16 mW of continuous power from the 65 μT RMS field of a 20 A RMS, 360 Hz structural current. A low-power sensor node platform with a custom multi-mode duty cycling network protocol is developed, offering cold starting network association and data acquisition/transmission functionality at 50 μW and 70 μW average power respectively. WSN level operation for 1 minute for every 8 minutes of energy harvesting is demonstrated. I. I

Federico Filippi, Giorgia Fiori, Gabriele Bocchetta, Salvatore Andrea Sciuto, Andrea Scorza
First experimental results of a novel arterial simulator with PWV adjustment

Pulse Wave Velocity (PWV) monitoring is a well-established method for both the diagnosis and prevention of cardiovascular diseases. Over the years, many arterial simulators have been made to study PWV dependency on the mechanical and geometrical characteristics of arterial surrogates; in particular, some of them are able to vary the tensional state of vessel walls to cause a change in PWV values. In this paper, a novel arterial simulator is presented, capable of varying the PWV of an arterial surrogate by acting independently on its inner and outer pressures. The simulator under assessment can manage pressures up to three times greater than the atmospheric one. This characteristic provides the possibility to explore many tensional states compared to its predecessors. The experimental outcomes confirm its working principle and an increasing trend in PWV is found. The result uncertainties are up to 10% of the corresponding PWV value. I

Giorgia Fiori, Gabriele Bocchetta, Maurizio Schmid, Silvia Conforto, Salvatore Andrea Sciuto, Andrea Scorza
Novel quality assessment protocol based on Kiviat diagram for pulsed wave Doppler diagnostic systems: first results

Ultrasound (US) systems are routinely and extensively used in several medical fields despite the lack of an internationally accepted quality standard for their testing. One crucial aspect for Quality Assessment (QA) protocols is the need to summarize the contribution of the large number of existing test parameters in a few meaningful quantities. The study herein proposed fits into this context, focusing on the use of the Kiviat diagram applied to Pulsed Wave Doppler (PWD) equipment QA. Four test parameters, derived from the literature, were objectively assessed through custom-written image analysis-based methods and then scaled for an effective combination. The experimental setup used to collect PWD spectrograms included an intermediate technology level US diagnostic system equipped with a linear array probe and a commercial Doppler flow phantom. Tests were repeated at two Doppler frequencies.

Jan Saliga, Pavol Kababik, Ondrej Kovac, Alena Pietrikova
Demonstration stand for non-destructive conductive material defect inspection by eddy current

To aid in the education of master's level electronic engineering students in our department, we have developed a simple stand that utilizes eddy currents for the non-destructive testing of conductive materials. This method is commonly used for detecting various cracks in the material. The purpose of the stand is to demonstrate the basic idea of such testing during laboratory exercises. The article details the design and implementation of the measuring stand, which includes a measuring device, reference test samples, and accessories. The measuring device is based on the myRIO DAQ device by NI and features a sensing probe that contains an excitation coil, a GMR magnetoresistor AA002-02, and a laser motion sensor. The control software for myRIO was developed in LabVIEW and utilizes both the processor and FPGA in myRIO.

Nikola Petrović, Lemana Spahić, Sanja Mandić, Platon Sovilj
Decoding Cognitive Processes in Arithmetic Tasks: An EEG-Based Convolutional Neural Network Model

– In this study, we introduce a novel system, developed in Python, for classifying cognitive processes based on EEG signals. The system employs a Convolutional Neural Network (CNN) trained on a dataset comprising 4-minute EEG recordings from 30 subjects. Each EEG sample processed for CNN input is 0.5 seconds long and is transformed into EEG power levels for each channel. The primary achievement of this research is the successful use of the CNN to classify whether a subject is performing a cognitive task well or poorly. The system's performance has been validated by experts in cognitive neuroscience and psychology, and its results have been benchmarked against state-ofthe-art studies in the field. This work represents a significant contribution to the field of EEG-based cognitive process classification, demonstrating the effective integration of machine learning techniques and neuroscience data.

Page 28 of 939 Results 271 - 280 of 9382