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International Conference on Prognostics and Health Management, PHM

作者： Daniel O. Williams Zhaojun Steven Li Afsaneh Ghanavati Industrial Engineering Department Western New England University Springfield MA USA Electrical and Computer Engineering Program School of Engineering Wentworth Institute of Technology Boston MA USA

With the current alarming exponential increase in global energy demand chiefly due to population growth, electrification, and the issues associated with fossil generation, utilities are reinvesting their returns in alternative ways of clean power generation. Although, finding alternative ways to provide clean energy and to advance the power grid are of the main interest globally, many countries face power theft as a frequent problem. in Ghana, power losses in the distribution system cost the nation over a billion Ghana Cedis in the country's total annual revenue, of which power theft plays a predominant role. This paper presents an electricity theft mitigation technique through a programmable smart energy meter. The proposed method is such that interruptions are added to the smart energy meters in order to detect input signals from an added current sensor placed at the terminal point of the service line, from where in-between the sensor and the meter, illegal connections are made. The proposed Advanced Metering Infrastructure (AMI) system will provide smart services, including calculating consumed energy in kWh and generating a bill sent to the utility station. After which, the AMI system will disconnect the power supply from the meter.

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Study of the relevance of gender in the classification of hand gestures by electromyography-based recognition systems

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Research on Biomedical engineering 2021年第2期37卷 361-373页

作者： Freitas, Melissa La Banca Junior, Jose Jair Alves Mendes La Banca, Wesley Freitas Stevan, Sergio Luiz Graduate Program in Electrical Engineering Federal University of Technology – Paraná Ponta GrossaParaná84016-210 Brazil Department of Electronics Federal University of Technology – Paraná CuritibaParaná80230-901 Brazil Mechanical Engineering Department Federal University of Technology – Paraná Ponta GrossaParaná84016-210 Brazil

Purpose: Some factors such as gender, age, physical fitness, and manual dominance are relevant and can influence the recognition of movement patterns using electromyography (EMG). In this scenario, we present an EMG signal analysis for men and women to observe if there is any significant difference. Methods: Data from 10 men and 10 women were acquired during the execution of six hand gestures (wrist flexion, wrist extension, wrist flexion to left, wrist extension to right, supination, and pronation) using eight channels armband. Four EMG time-domain signal features were extracted and hand gestures were classified using linear and quadratic discriminant analysis (LDA, QDA), and k-nearest neighbors (KNN) algorithms. Results: Data of the feature difference absolute standard deviation value (DASDV) and waveform length (WL) were analyzed based on polar and bar graphs. KNN with 1 nearest neighbor obtained the best results between the classifiers for both men and women. For statistical analyses, the Wilcoxon-Mann-Whitney and Tukey post hoc in Friedman tests were used. The results show that there is no significant difference between data from different genders. Conclusion: After analyzing the results obtained and extensive comparison with related works, it was concluded that, for the conditions where the electrodes are positioned equidistantly, evaluating all the muscular groups of a limb (armband format), there was no significant difference observed between the data from different genders. In addition, this allows us to conclude that EMG armband on the forearm can be a good option for robotic systems control without the need for prior gender adjustment. © 2021, Sociedade Brasileira de Engenharia Biomedica.

关键词： Biomedical signal processing

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Feature Extraction of Internal Fault Types for the Solar PV System using the Novel NIFM Techniques

Feature Extraction of Internal Fault Types for the Solar PV ...

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Power and electrical engineering (ACPEE), 5th Asia Conference on

作者： Hsueh-Hsien Chang Ren-Rong Guo Ching-Lung Lin Bachelor Program of Wind Power Minghsin University of Science and Technology Hsinchu Taiwan R.O. C. Dept. Electrical Engineering Program B Yuan Ze University Taoyuan Taiwan R.O. C. Dept. Electrical Engineering Minghsin University of Science and Technology Hsinchu Taiwan R.O. C.

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

In low-voltage solar grids, traditional fault analysis and monitoring systems are used to detect power faults. These include wide-area protection technology with GPS and phasor measurement units (PMUs) and protective relays at each transmission line end. However, these designs increase data complexity and system cost. This paper uses the non-intrusive load identification technology, which involves installing a measuring device at the entrance of the extra high-voltage (EHV) transmission network. The measurement signal is processed by a proposed feature extraction method to form power energy features of various fault types in the frequency domain of the internal line of the low-voltage solar photovoltaic power grid. This approach is not only easier to install, but it is also more cost-effective. The results of the proposed method show the apparent differences for the different fault types.

关键词： Photovoltaic systems Low voltage Protective relaying Feature extraction Transmission line measurements Power grids Phasor measurement units

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Speech Abusive Language Detection System Using MFCC Speech Feature Extraction and Convolutional Neural Network

Speech Abusive Language Detection System Using MFCC Speech F...

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Consumer technology (ICCT-Pacific), International Conference on

作者： Yi-Chang Zhu Ying-Hsiu Hung Yen-Ching Chang Jhen-Kai Tang Wen-Kai Tsai Shin-Chi Lai The Doctoral Degree Program in Smart Industry Technology Research and Development National Formosa University Huwei Taiwan Dept. Electronics Engineering National Yunlin University of Science and Technology Douliu Taiwan Doctoral Degree Program in Smart Industry Technology Research and Development National Formosa University Huwei Taiwan Department of Electrical Engineering Master's Program National Formosa University Huwei Taiwan Dept. Electrical Engineering National Formosa University Huwei Taiwan Dept. Automation Engineering & Smart Machinery and Intelligent Manufacturing Research Center National Formosa University Huwei Taiwan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

As bullying rapidly spreads in schools, many parents are becoming increasingly concerned about their children being subjected to bullying by peers, which could negatively impact their physical and mental health. This paper proposes an abusive language detection system that combines Mel-frequency Cepstrum Coefficients (MFCC) speech features with a Convolutional Neural Network (CNN). Audio files which contain daily abusive phrases in the Minnan dialect are initially preprocesses to eliminate non-speech interference. Subsequently, the MFCC algorithm is applied to extract speech features that closely capture auditory characteristics. The CNN classification model is trained to learn the MFCC features and classify the phrases into their respective categories. Experimental results indicate that the CNN model achieves an average recognition accuracy of 91.9%. Finally, the CNN model was deployed on an embedded platform, where it achieves an average recognition time of 0.54 seconds per phrase and an average recognition accuracy of 86.25%.

关键词： Pediatrics Accuracy Semantics Speech recognition Mental health Speech enhancement Feature extraction Convolutional neural networks Mel frequency cepstral coefficient Optimization

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Experimental Evaluation of Commercial Powerline Communication System for Monitoring of Sensors in Industrial Processes

Experimental Evaluation of Commercial Powerline Communicatio...

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Mediterranean Electrotechnical Conference (MELECON)

作者： Murilo Oliveira Leme Sergio Luiz Stevan Department of Electronics UTFPR-PG Federal University of Technology -Parana (UTFPR) Ponta Grossa Brazil Postgraduate Program in Electrical Engineering - PPGEE Federal University of Technology - Parana (UTFPR) Ponta Grossa Brazil

ISBN: (数字)9798350387025

ISBN: (纸本)9798350387032

Industrial automation systems use distributed computing architecture, comprising industrial networks with a wiring bus that is standardized to integrate their devices and monitoring process. A number of technologies, in a wide range of application levels, must operate in hostile environments, with high temperatures, humidity and magnetic interference. The Industry 4.0 applications requires that the communication infrastructure provide "last mile" communication services with a high level of reliability, which may increase costs and complexity of that infrastructure. Within such scenario, there is a growing demand for simpler and robust systems for monitoring and supervision of industrial processes. Powerline communication (PLC) is one of such systems that could provide ease of use and maintenance, since it uses the power system for serial digital data communication. This system has been commonly used in home applications, but it carries a great potential for the management of an industrial plant. Here, we present a new concept for the hardware, which collects field signals with PLC for industrial applications, using a Commercial-Of-The-Shelf (COST) modem. Three different setups have been performed, for a specific application that could be integrated to any industrial computer. The system has been experimentally evaluated in severe industrial environments, considering different noise levels, and provided reliable communication.

关键词： Wiring Costs Wireless networks Interference Sensor systems Sensors Power system reliability

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Optical Fiber Coiled Sensors for Acoustic Oblique Wave Detection using Distributed Acoustic Sensing

Optical Fiber Coiled Sensors for Acoustic Oblique Wave Detec...

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IEEE SENSORS

作者： Frederico A. Jahnert Beatriz Brusamarello Danilo F. Gomes Sérgio T. de Camargo Manoel F. da Silva Jean C. Cardozo da Silva Cicero Martelli Jucélio T. Pereira Carlos A. Bavastri Graduate Program in Mechanical Engineering Federal University of Parana (UFPR) Curitiba Brazil Graduate Program in Electrical and Computer Engineering Federal University of Technology-Paraná (UTFPR) Curitiba Brazil Petrobras Research and Development Program Rio de Janeiro Brazil

Distributed Acoustic Sensors (DAS) are able to measure dynamic strain and temperature signals quantitatively along several kilometers of optical fiber using the properties of backscattering light. A drawback of DAS is the sensing resolution of around 1 meter long. This paper analyses the use of DAS as a vibration sensor for a thin plate structure using an acoustic excitation. A coiled method of arranging the sensing optical fibers enhances the measured signal and using a calibration method, the strain in the sensed region is obtained. The method can be used to characterize structures acoustically allowing the structure to detect the direction and reconstruct nearby acoustic events. Acoustic excitations were performed using a speaker at 1 meter distance to a 1 millimeter thick free-free 40 centimeters by 73 centimeter instrumented stainless steel plate inside an anechoic chamber. Results measured using reference microphones and accelerometers were compared to the optical fiber sensor through a Finite Element Model. The results demonstrate that the optical fiber system is able to measure the frequency response with an average 54 dB sound pressure level sound source chirp signal for flexural modes with a clear differentiation between angles of incidence up to 500 Hz.

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Linear Fresnel collector (LFC) for enhancing solar water desalination process 8

Linear Fresnel collector (LFC) for enhancing solar water des...

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8th International engineering Conference on Renewable Energy and Sustainability, ieCRES 2023

作者： El-Khozondar, Hala J. Elnaggar, Mohamed Elnaggar, Mohamed Ellouh, Ahmed Omar Alghaffari, Mahmoud Walid Nassar, Hamza Bassam Alnahhal, Mohammed Islamic University of Gaza Electrical Engineering and Smart Systems Department Palestine Palestine Technical College - Deir El-Balah Engineering Program Department Palestine Wadi Alshatti University Mechanical & Renewable Energy Eng. Dept Brack Libya Al-Azhar University Renewable Energy Engineering Department Gaza Palestine Islamic University of Gaza Mechanical Engineering Department Palestine Israa University-Palestine Faculty of Engineering and Information Technology Palestine

ISBN: (纸本)9798350300758

The limited availability of clean water resources in Gaza Strip is due to the increasing salinity of groundwater, which is due to unbalanced consumption. Furthermore, the increase in the poverty level among the people and the lack of fossil fuel resources, and the high intensity of solar radiation in the strip have grabbed the attention of the authors to think about a suitable alternative to produce potable water via solar energy. This study aims to investigate the linear Fresnel collector (LFC) coupled with a solar still-single effect active system. The solar still was designed to match the LFC output to avoid any heat losses that may decrease the system's effectiveness. A CFD simulation was carried out using Ansys Fluent software to predict temperature and pressure distributions to find out the efficiency of the LFC collector. The results showed that the use of LFC leads to an increase in the efficiency of the solar still, and the daily production of distilled water reaches 1.5 Litre /m2 © 2023 IEEE.

关键词： Potable water

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Analysis of the Brazilian Climate Data Influence on Soybean Pricing by Using Long Short-Term Memory Models

SSRN

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SSRN 2024年

作者： Oliva, Jefferson Tales Martelli, Otávio Pigozzo de Castro Barbosa, Marco Antônio Dal Molin, Viviane Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical and Computer Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Department of Academic Informatics Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil Graduate Program in Production and Systems Engineering Federal University of Technology-Paraná PR Pato Branco85503-390 Brazil

This work uses machine learning to verify whether the Brazilian climate influences international soybean price prediction. For this, climatic data, dollar quotes, inflation, and annual soybean production were collected from different data sources. Then, the collected data were pre-processed and grouped by Brazilian state. Afterward, data from the five most productive Brazilian states are chosen, such as Mato Grosso (MT), Mato Grosso do Sul (MS), Goiás (GO), Paraná (PR), and Rio Grande do Sul (RS). Afterward, predictive models are built using the long short-term memory (LSTM) method, which is applied in each chosen state dataset considering two different settings: with and without climatic data. Thus, two models were built for each Brazilian state, totaling ten predictors. In the experimental evaluation, when trained with climatic data, the PR model achieved the lowest values of root mean squared error (RMSE) and mean absolute error (MAE). Regarding predictors trained without climate data, the RS and PR obtained the lowest values of RMSE and MAE, respectively. After conducting statistical hypothesis tests, no significant difference was found among models, stating, with 95% certainty, that, in this study, the Brazilian climatic data did not influence the model performance for predicting soybean prices. On the other hand, one of the main contributions of work is conducting an unprecedented study about soybean price prediction using Brazilian climatic data. © 2024, The Authors. All rights reserved.

关键词： Long short-term memory

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Tactile Displays Driven by Projected Light

arXiv

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arXiv 2024年

作者： Linnander, Max Goetz, Dustin Reardon, Gregory Kumar, Vijay Hawkes, Elliot Visell, Yon Department of Mechanical Engineering United States Department of Bioengineering United States Media Arts & Technology Program United States Department of Electrical and Computer Engineering University of California Santa Barbara United States

Tactile displays that lend tangible form to digital content could transform computing interactions. However, achieving the resolution, speed, and dynamic range needed for perceptual fidelity remains challenging. We present a tactile display that directly converts projected light into visible tactile patterns via a photomechanical surface populated with millimeter-scale optotactile pixels. The pixels transduce incident light into mechanical displacements through photostimulated thermal gas expansion, yielding millimeter scale displacements with response times of 2 to 100 milliseconds. Employing projected light for power transmission and addressing renders these displays highly scalable. We demonstrate optically driven displays with up to 1,511 addressable pixels – several times more pixels than any prior tactile display attaining comparable performance. Perceptual studies confirm that these displays can reproduce diverse spatiotemporal tactile patterns with high fidelity. This research establishes a foundation for practical, versatile high-resolution tactile displays driven by light. Copyright © 2024, The Authors. All rights reserved.

关键词： Light transmission

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Local Sequential MCMC for Data Assimilation with Applications in Geoscience

arXiv

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arXiv 2024年

作者： Ruzayqat, Hamza Knio, Omar Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

This paper presents a new data assimilation (DA) scheme based on a sequential Markov Chain Monte Carlo (SMCMC) DA technique [36] which is provably convergent and has been recently used for filtering, particularly for high-dimensional non-linear, and potentially, non-Gaussian state-space models. Unlike particle filters, which can be considered exact methods and can be used for filtering non-linear, non-Gaussian models, SMCMC does not assign weights to the samples/particles, and therefore, the method does not suffer from the issue of weight-degeneracy when a relatively small number of samples is used. We design a localization approach within the SMCMC framework that focuses on regions where observations are located and restricts the transition densities included in the filtering distribution of the state to these regions. This results in immensely reducing the effective degrees of freedom and thus improving the efficiency. We test the new technique on high-dimensional (d ∼ 104 − 105) linear Gaussian model and non-linear shallow water models with Gaussian noise with real and synthetic observations. For two of the numerical examples, the observations mimic the data generated by the Surface Water and Ocean Topography (SWOT) mission led by NASA, which is a swath of ocean height observations that changes location at every assimilation time step. We also use a set of ocean drifters' real observations in which the drifters are moving according the ocean kinematics and assumed to have uncertain locations at the time of assimilation. We show that when higher accuracy is required, the proposed algorithm is superior in terms of efficiency and accuracy over competing ensemble methods and the original SMCMC *** Codes 62M20, 60G35, 60J20, 94A12, 93E11, 65C40 © 2024, CC BY.

关键词： Markov chains

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