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Finite Element Analysis Study of FBG Magnetostrictive Composite Flux sensor Geometry for Electric Motor Air-gap Flux Monitoring 11

Finite Element Analysis Study of FBG Magnetostrictive Compos...

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11th Mediterranean conference on Embedded Computing (MECO) / 3rd Summer School on Cyber-Physical + systems and Internet of Things (CPS and IoT)

作者： Suryandi, Asep Andi Tuohy, Paul Djurovic, Sinisa Univ Manchester PTIP TIRBR Natl Res & Innovat Agcy BRIN Dept Elect & Elect Engn Manchester Lancs England Univ Manchester Dept Elect & Elect Engn Manchester Lancs England

ISBN: (纸本)9781665468282

With the progressively more prominent usage of electric motors in a wide range of applications, more advanced monitoring of their operating parameters is becoming increasingly important. The in-service observation of the airgap magnetic flux can be very useful for monitoring the status of permanent magnets, which are key to most modern motors' performance. This was recently shown to be possible through the in-situ application of magnetostrictive composite fibre optic flux sensors. This paper reports an electromagnetic finite element model study exploring the performance of various such sensor configurations and positions in the air-gap of a commercial motor design. The aim of the model study is to identify sensor design and positioning features that can yield an enhanced response in observation of rotor flux. It is shown that rectangular cross-sectional flux sensor geometries provide a considerable advantage in this respect.

关键词： PM motors Finite Element Analysis FBG sensor permanent magnets magnetostrictive composite material terfenol-D powder

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Relative Localization for Real-time Adaptive Quadruped Mobile Projector System

Relative Localization for Real-time Adaptive Quadruped Mobil...

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International conference on Display Technology, 2024

作者： Gao, Qiangsheng Cheng, Ka Ho Li, Anran Liu, Yibo The Hong Kong University of Science and Technology Hong Kong State Key Laboratory of Advanced Displays and Optoelectronics Technologies and Centre for Display China

The technology of home projectors has matured significantly. However, most projectors are limited to static manual projectors, and projectors capable of automatic focusing and keystone correction are expensive. Furthermore, there is still room for development in the adaptability and real-time performance of the screen distance and spatial angle measurement systems that projectors use for automatic focusing and keystone correction. Compared with the existing laser focusing technology, in this research, we present an alternative solution to acquire real-time screen distance and spatial angle estimations using relative localization algorithms and an ultrasonic ranging sensor array. The relative localization information can then be employed for automatic focusing and keystone correction of a projector mounted on the mobile platform of an open-source quadruped robot. The proposed approach will enhance the versatility and adaptability of the projector system, providing an economical solution for realtime automatic focusing and keystone correction in mobile projector platforms. © 2024 John Wiley and Sons Inc. All rights reserved.

关键词： Real time systems

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Enhanced walk on spheres algorithm with generative adversarial networks for convection-diffusion simulation 4

Enhanced walk on spheres algorithm with generative adversari...

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4th International conference on advanced Algorithms and Neural Networks, AANN 2024

作者： Yang, Qiaochu The University of Hong Kong Hong Kong

ISBN: (纸本)9781510686106

This study introduces an enhanced Walk on Spheres (WOS) algorithm, integrated with Generative Adversarial Networks (GANs), to simulate convection-diffusion processes involving velocity fields. The traditional WOS algorithm handles isotropic diffusion well but struggles with convection-diffusion scenarios. By training GANs to generate spherical distribution data, the extended WOS algorithm adapts to varying boundary conditions and convection influences. Our approach segments the computational domain into multiple radial intervals, training a specific GAN model for each interval to capture particle dynamics accurately. This segmentation allows the algorithm to select the most suitable model in real-time, enhancing simulation accuracy and adaptability. Experimental results show significant improvements in computational efficiency and accuracy compared to traditional Monte Carlo methods, with the enhanced WOS algorithm reducing runtime by approximately 40% while maintaining high precision. The algorithm’s robustness and flexibility make it valuable for various applications, including ecological dynamics, disease modeling, and fluid dynamics. Future work will focus on optimizing the algorithm for highly irregular media and expanding its application to broader scientific and engineering problems. © 2024 SPIE.

关键词： Monte Carlo methods Computer simulations Particles Optical spheres Gallium nitride Diffusion Convection Mathematical optimization Boundary conditions systems modeling

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Unified ensemble federated learning with cloud computing for online anomaly detection in energy-efficient wireless sensor networks

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JOURNAL OF CLOUD COMPUTING-ADVANCES systems AND applications 2024年第1期13卷 49-49页

作者： Gayathri, S. Surendran, D. Bannari Amman Inst Technol Dept Comp Sci & Engn Sathyamangalam 638401 Tamil Nadu India Karpagam Coll Engn Othakkal Mandapam Dept Informat Technol Coimbatore 641032 Tamil Nadu India

Anomaly detection in Wireless sensor Networks (WSNs) is critical for their reliable and secure operation. Optimizing resource efficiency is crucial for reducing energy consumption. Two new algorithms developed for anomaly detection in WSNs-Ensemble Federated Learning (EFL) with Cloud Integration and Online Anomaly Detection with Energy-Efficient Techniques (OAD-EE) with Cloud-based Model Aggregation. EFL with Cloud Integration uses ensemble methods and federated learning to enhance detection accuracy and data privacy. OAD-EE with Cloud-based Model Aggregation uses online learning and energy-efficient techniques to conserve energy on resource-constrained sensor nodes. By combining EFL and OAD-EE, a comprehensive and efficient framework for anomaly detection in WSNs can be created. Experimental results show that EFL with Cloud Integration achieves the highest detection accuracy, while OAD-EE with Cloud-based Model Aggregation has the lowest energy consumption and fastest detection time among all algorithms, making it suitable for real-time applications. The unified algorithm contributes to the system's overall efficiency, scalability, and real-time response. By integrating cloud computing, this algorithm opens new avenues for advanced WSN applications. These promising approaches for anomaly detection in resource constrained and large-scale WSNs are beneficial for industrial applications.

关键词： Wireless sensor networks Online anomaly detection Energy efficiency Federated learning Machine learning Cloud computing

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System Architecture for a Wireless sensor Network for Sustainable Agriculture, Forestry and Green Spaces in Smart Cities

System Architecture for a Wireless Sensor Network for Sustai...

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IEEE International Workshop on Intelligent Data Acquisition and advanced Computing systems: Technology and applications

作者： Sebastian Rosewick Felix Schorlemer Frank Kunemund Department of Computer Science Fachhochschule Dortmund

This paper presents a wireless sensor network employing heterogeneous mobile robot platforms designed for data-acquisition and research in agriculture, forestry and green spaces in smart cities. Where conventional sensor networks struggle with a lack in flexibility, little variation in their reading points and no possibilities in mobile manipulation, this approach offers new capabilities in accomplishing complex tasks in outdoor and indoor scenarios. A wheel driven robot platform in combination with multiple UAVs 1 1 Unmanned Aerial Vehicle forms the basis for the mobile sensor network which can make use of a wide variety of sensors and actuators. The system benefits from new developments in controlling multi-agent systems as well as machine-learning-algorithms for local and independent data-analysis.

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Mecanum wheel mobile platform for rapid prototyping of the autonomous control algorithms 18

Mecanum wheel mobile platform for rapid prototyping of the a...

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18th IFAC conference on Programmable Devices and Embedded systems (PDES)

作者： Jaroszewicz, Kacper Walendziuk, Wojciech Trochimczuk, Roman Wolniakowski, Adam Tomaszewki, Radoslaw Slanina, Zdenek Bialystok Tech Univ Doctoral Sch Bialystok Poland Bialystok Tech Univ Dept Electrotech Power Elect & Elect Power Engn Bialystok Poland Bialystok Tech Univ Dept Automat Control & Robot Bialystok Poland VSB Tech Univ Ostrava 17 Listopadu 2172-15 Ostrava Czech Republic

This article describes the author's design of the Mecanum wheel mobile robots (MWR), which can be used as a test platform for experimental research into the development and implementation of autonomous systems. The paper contains a literature review of the subject matter and describes the mechanical actuator subsystem and electronic and information subsystem of the mobile robot solution. The robot was navigated using a minicomputer equipped with a Jetson Nano chip. The robot's navigation system was implemented using the ROS environment through high-level software. Software modularity is desirable in circuits intended for research and rapid prototyping. This allows for easier modification and maintenance. The microcontroller has been implemented with a DC drive control system and incremental encoder support to estimate robot position using odometry. The project utilizes the Jetson Nano for processing data from distance sensors and monitoring the robot's performance. The mobile platform is equipped with a RGB-D camera (Microsoft Kinect 360), the robot can use this to perform 3D mapping of the environment. A LiDAR sensor is used to collect data from a two-dimensional space. Laboratory tests were carried out to test the validity of the solutions adopted in the design of the Mecanum-wheeled mobile robot's navigation system configuration. Copyright (c) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： autonomous systems Mecanum wheels robot (MWR) Microsoft Kinect 360 LiDAR sensor

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Efficient Compression of Reactor Vessel Monitoring sensor Data using Machine Learning

Efficient Compression of Reactor Vessel Monitoring Sensor Da...

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2023 Transactions of the American Nuclear Society Winter conference and Expo, ANS 2023

作者： Pantopoulou, Stella Anthonie, Cilliers Tsoukalas, Lefteri Heifetz, Alexander ArgonneNational Laboratory Nuclear Science and Engineering Division LemontIL60439 United States Schoolof Nuclear Engineering Purdue University West LafayetteIN47906 United States Kairos Power AlamedaCA94501 United States

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A Heterogeneous Multi-RISCV Architecture for Image Processing and Computer Vision applications 12

A Heterogeneous Multi-RISCV Architecture for Image Processin...

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2024 IEEE Andescon conference

作者： Lima, Arthur M. Silva, Douglas L. Santos, Hercules I. A. Arias-Garcia, Janier Beserra, Gilmar S. Yudi, Jones Univ Brasilia Automat & Control Grp Brasilia DF Brazil Univ Fed Minas Gerais Dept Elect Engn Belo Horizonte MG Brazil Univ Brasilia Fac Gama Brasilia DF Brazil

ISBN: (纸本)9798350355291;9798350355284

In the advanced field of Image Processing and Computer Vision (IP/CV), there is a trend toward utilising parallel processing in computer architectures for enhanced efficiency, striking a balance between general-purpose capabilities and hardware-specific processes. The RISC-V standard, now backed by a wide array of compilers, frameworks, and operating systems, is paving the way for innovative cores. Our introduction of a Multi-Processor systems on Chip (MPSoC), MPRISC-V, is a testament to this evolution. This system incorporates a Network on Chip (NoC) for robust intra-chip communication. The Processing System (PS) seamlessly integrates and manages it through a user-friendly API crafted to simplify the development cycle. To ascertain its effectiveness, we tested it on a Zynq Ultrascale+ MPSoC device, deploying a Sobel-based application benchmark. By evaluating its efficiency in terms of cycles/pixels, our findings underscore its potential and spotlight areas ripe for further enhancement.

关键词： MPSoC IP/CV RISC-V Sobel-filter FPGA

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Guest Editorial Special Issue on Selected Papers From the IEEE sensors 2019 conference

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IEEE sensorS JOURNAL 2021年第8期21卷 9634-9635页

作者： Vida, Rolland Budapest Univ Technol & Econ HSN Lab Budapest Hungary Budapest Univ Technol & Econ Budapest Hungary

IEEE sensors is the flagship conference of the IEEE sensors Council, attracting each year more than 800 paper submissions, on diverse topics related to sensing technologies, sensors devices, systems, and communications. The IEEE sensors 2019 conference was held in Montreal, QC, Canada, on October 27–30, 2019, and featured a program with 13 regular tracks and three focused sessions. The regular tracks targeted areas such as sensor phenomenology, modeling and evaluation, sensor materials, processing and fabrication (including printing), chemical, electrochemical, and gas sensors, microfluidics and biosensors, optical sensors, physical sensors, temperature, mechanical, magnetic and other sensors, acoustic and ultrasonic sensors, sensor packaging (including flexible materials), sensor networks (including IoT and related areas), emerging sensor applications, sensor systems: signals, processing and interfaces, as well as actuators and sensor power systems. One track was dedicated specifically to sensors in industrial practices. The three focused sessions targeted areas such as engineering in medical diagnostics and therapeutics, biomedical sensors based on electromagnetics, and flexible and printed IoT sensors.

关键词： Special issues and sections Meetings sensor systems sensor phenomena and characterization Gas detectors sensors

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HTIDB: Hierarchical Time-Indexed Database for Efficient Storage and Access to Irregular Time-series Health sensor Data 44

HTIDB: Hierarchical Time-Indexed Database for Efficient Stor...

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44th Annual International conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Scott, Grant J. Saied-Walker, Jamal Marchal, Noah Yu, Hang Skubic, Marjorie Univ Missouri Dept Elect Engn & Comp Sci Columbia MO 65211 USA Univ Missouri Ctr Eldercare & Rehabil Technol Columbia MO 65211 USA

ISBN: (数字)9781728127828

ISBN: (纸本)9781728127828

With the enormous amount of data collected by unobtrusive sensors, the potential of utilizing these data and applying various multi-modal advanced analytics on them is numerous and promising. However, taking advantage of the ever-growing data requires high-performance data-handling systems to enable high data scalability and easy data accessibility. This paper demonstrates robust design, developments, and techniques of a hierarchical time-indexed database for decision support systems leveraging irregular and sporadic time series data from sensor systems, e.g., wearables or environmental. We propose a technique that leverages the flexibility of general purpose, high-scalability database systems, while integrating data analytics focused column stores that leverage hierarchical time indexing, compression, and dense raw numeric data storage. We have evaluated the performance characteristics and tradeoffs of each to understand the data access latencies and storage requirements, which are key elements for capacity planning for scalable systems.

关键词： Decision support systems Data analysis Wearable computers Scalability Time series analysis Memory sensor phenomena and characterization

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