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Fault Diagnosis for a Three-Wheel Omidirectional Vehicle: A Geometric Approach 17

Fault Diagnosis for a Three-Wheel Omidirectional Vehicle: A ...

引用

17th international conference on electrical engineering, computing science and automatic control, CCE 2020

作者： Lizarraga, Adrian Begovich, Ofelia Ramirez, Antonio Cinvestav Dep. of Electrical Engineering Guadalajara Mexico

ISBN: (纸本)9781728189871

This work presents a fault diagnoser for a three-wheel omnidirectional vehicle, which is based on the FDI (Fault Detection and Isolation) approach proposed by Massoumnia [1]. It is designed for a linearized model of the vehicle (mobile robot). More precisely, this diagnoser will detect and locate actuator's faults, when the velocities and orientation angle of the robot are considered constants then, the efficiency of the proposed method is evaluated on the nonlinear model of the vehicle. By virtue of the method, it is capable to locate both concurrent and non-concurrent faults. © 2020 IEEE.

关键词： Mobile robots

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Semantic Features Extraction for Anomaly Detection from Real-World Videos*

Semantic Features Extraction for Anomaly Detection from Real...

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IEEE international conference on Research, Innovation and Vision for the Future

作者： Minh-Hanh Tran Thanh-Hai Tran School of Electrical and Electronic Engineering Hanoi University of Science and Technology Hanoi Vietnam

Video-based anomaly detection opens up numerous practical applications such as video surveillance and healthcare. Despite having been studied for an extended period, this problem remains highly challenging because of variations in anomalies caused by people, objects, or contexts. Furthermore, the issue of missing annotated datasets and imbalances in the training data can complicate the development of automatic detection systems. Moreover, many existing systems have attempted to detect anomalies by performing binary classification without providing any explanation of the results. This paper proposes a method to detect anomalies from video while providing a semantic explanation of the cause. We first deploy off-the-shelf techniques to detect people and objects in the scene, then we extract semantic features (motion, appearance, posture) to recognize anomalies. To focus more on posture change, we introduce new postural descriptions and time series descriptions of poses using a spatiotemporal graph convolutional neural network. The proposed method is validated on three public datasets: UCSD Ped2, CUHK Avenue, and ShanghaiTech Campus showing improvements over the baseline methods.

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Harnessing Resource and Demand Flexibility for Energy Management in Urban Micro-grids 11

Harnessing Resource and Demand Flexibility for Energy Manage...

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11th international conference on Innovative Smart Grid Technologies - Asia, ISGT-Asia 2022

作者： Subramanian, Lalitha Jiyan, Wu Tjandra, Rudy Troitzsch, Sebastian Massier, Tobias Teh, Erine Siew Pheng Migne, Romain Yan, Xu EDF Lab Singapore Singapore TUMCREATE Ltd. Singapore Singapore Institute of Technology Engineering Cluster Singapore Institute for High Performance Computing Agency for Science Technology and Research Singapore Singapore Institute of Technology Chemical Engineering and Food Technology Cluster Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (纸本)9798350399660

Successful adoption of distributed clean energy resources requires the enhancement of system flexibility from both the generation and the demand side. This paper presents a case study on the Punggol Digital District of Singapore exploring both distributed generation, storage, and demand side flexibility. The distributed generation resources investigated include rooftop photovoltaic systems and waste-to-electricity generation via hydrogen and fuel cell technology. In the urban use case, the local demand to be served far exceeds the local distributed clean energy generation potential. Therefore in this context, flexibility is the key added value of collective self-consumption, which could be leveraged as a valuable grid service in the city-state to support the integration of variable renewable energy resources. In this context, this work presents the assessment of the flexibility that can be provided by the cooling demand and electric vehicles by the control of respective demand-side resources. © 2022 IEEE.

关键词： Energy management

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Parity Shadow Stack: Dynamic Instrumentation based control Flow Security for IoT Devices

Parity Shadow Stack: Dynamic Instrumentation based Control F...

引用

IEEE international conference on Performance, computing and Communications (IPCCC)

作者： Charles Qing Cao Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA

One of the challenges in ensuring the security of Internet of Things (IoT) devices involves preserving control flow integrity (CFI) against return-oriented programming (ROP) attacks. Traditional defense mechanisms, while effective, often require substantial changes to the compiler, thereby limiting their applicability to a broad range of devices. To overcome this challenge, we present the Parity Shadow Stack — a novel, compact shadow stack mechanism that leverages dynamic instrumentation and binary rewriting to achieve similar effects compared to compiler-based methods. Further, this method does not require application source code and can work with legacy applications where only the binary is available. Finally, we demonstrate that it is more flexible as it provides a programming interface to add additional security semantics checks. Through our evaluations, we find that our method introduces a remarkably low overhead, less than 10 percent for medium-size or large-size applications. Therefore, we conclude it provides robust and practical defense against ROP attacks without requiring source code or compiler changes, nor does it require any specialized hardware.

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UbiEi-Edge: Human Big Data Decoding Using Deep Learning on Mobile Edge 43

UbiEi-Edge: Human Big Data Decoding Using Deep Learning on M...

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43rd Annual international conference of the IEEE-engineering-in-Medicine-and-Biology-Society (IEEE EMBC)

作者： Zou, Jiadao Zhang, Qingxue Indiana Univ Purdue Univ Purdue Sch Engn & Technol Dept Elect & Comp Engn Joint Campus Purdue Univ & Indiana Univ Indianapolis IN 46202 USA

ISBN: (纸本)9781728111797

Human big data decoding is of great potential to reveal the complex patterns of human dynamics like physiological and biomechanical signals. In this study, we take special interest in brain visual dynamics, e.g., eye movement signals, and investigate how to leverage eye signal decoding to provide a voice-free communication possibility for ALS patients who lose ability to control their muscles. Due to substantial complexity of visual dynamics, we propose a deep learning framework to decode the visual dynamics when the user performs eye-writing tasks. Further, to enable real-time inference of the eye signals, we design and develop a mobile edge computing platform, called UbiEi-Edge, which can wirelessly receive the eye signals via low-energy Bluetooth, execute the deep learning algorithm, and visualize decoding results. This real word implementation, developed on an Android Phone, aims to provide real-time data streaming and automatic, real-time decoding of brain visual dynamics, thereby enabling a new paradigm for ALS patients to communicate with the external world. Our experiment has demonstrated the feasibility and effectiveness of the proposed novel mobile edge computing prototype. The study, by innovatively bridging AI, edge computing, and mobile health, will greatly advance the brain dynamics decoding-empowered human-centered computing and smart health big data applications.

关键词： Health Informatics Edge computing Mobile Health Electrooculography Big Data

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Power Quality Enhancement in Transmission System Using Proposed Switched Capacitor Multilevel Inverter-Based Static Synchronous Compensator 2nd

Power Quality Enhancement in Transmission System Using Propo...

引用

2nd international conference on Electronic Systems and Intelligent computing, ESIC 2021

作者： Ramya, G. Suresh, P. Manimaran, B. EEE Department SRM Institute of Science & Technology Ramapuram Chennai India EEE Department St. Joseph College of Engineering Sriperumbudur Chennai India EEE Department Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9789811694875

Power quality enhancement in transmission system proposes the new structure of Switched Capacitor Multilevel Inverter (SCMLI)-based Static Synchronous Compensator (STATCOM) to improve the power quality. SCMLI can generate voltage sources with the least number of components for symmetric and asymmetric values. The proposed system consists of a DC converter with a switched capacitor to operate as a self-balancing device using an asymmetrical binary algorithm. Switched Capacitor Multilevel Inverter can generate 21 level Multilevel output from DC source. This scheme is applied to STATCOM for improving compensation ability, suppression of harmonics, and reactive power control under non-linear load conditions. Proposed SCMLI-based STATCOM is employed in both single and three phase transmission system and is simulated using MATLAB Simulink and verified with PIC controller-based hardware implementation. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Static synchronous compensators

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Solar PV Charge controller with Battery Management System Using Voltage Reference control 4

Solar PV Charge Controller with Battery Management System Us...

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4th IEEE international conference on computing, Power and Communication Technologies, GUCON 2021

作者： Prakash, Deep Raiker, Gautam A. Agrawal, Shubham Subba Reddy, B. Indian Institute of Science Electrical Engineering Bangalore560012 India ICER Interdisciplinary Center for Energy Research Indian Institute of Science Bangalore560012 India ICER Indian Institute of Science Bangalore560012 India

ISBN: (纸本)9781728199511

Solar power is a great alternative to existing power sources. Global warming will lead to a lack of power sources soon. With the rapid increase of electrical power in the atmosphere, it is necessary to take strong steps to manage it. Solar power is affected by the weather. The development of solar charge controllers is therefore necessary. The solar charge controller connects the load between the photovoltaic panel and the battery. During the day, the PV panel supplies the load as well as charges the battery, and during the night, the battery supplies the load. By using the solar charge controller, the PV panel will operate at MPPT (Maximum Power Point Tracking), and the battery will be protected from damage (undercharging and overcharging) by checking its state of charge. Variable and constant DC supplies can be supported by the charge controller. DC nano grids, solar-powered electric vehicles, and thermoelectric modules for heating and cooling can benefit from this technology. © 2021 IEEE.

关键词： Solar panels

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CNN-Based Estimation of Water Depth from Multispectral Drone Imagery for Mosquito control

CNN-Based Estimation of Water Depth from Multispectral Drone...

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IEEE international conference on Image Processing

作者： Qianyao Shen K.T.Y. Mahima Kasun De Zoysa Luca Mottola Thiemo Voigt Markus Flierl Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden School of Computing University of Colombo Sri Lanka RISE Research Institutes of Sweden Sweden Department of Electrical Engineering Uppsala University Sweden

We present a machine learning approach that uses a custom Convolutional Neural Network (CNN) for estimating the depth of water pools from multispectral drone imagery. Using drones to obtain this information offers a cheaper, timely, and more accurate solution compared to alternative methods, such as manual inspection. This information, in turn, represents an asset to identify potential breeding sites of mosquito larvae, which grow only in shallow water pools. As a significant part of the world’s population is affected by mosquito-borne viral infections, including Dengue and Zika, identifying mosquito breeding sites is key to control their spread. Experiments with 5-band drone imagery show that our CNN-based approach is able to measure shallow water depths accurately up to a root mean square error of less than 0.5 cm, outperforming state-of-the-art Random Forest methods and empirical approaches.

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Smart Grid Tolerance Invasion control Under False Data Injection Attacks 8th

Smart Grid Tolerance Invasion Control Under False Data Injec...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

作者： Li, Ming Wei, Lisheng Wang, Ruiren Anhui Key Laboratory of Electric Drive and Control Anhui Polytechnic University Wuhu241000 China School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China

ISBN: (纸本)9789819602247

Aiming at the problem of how to maintain stable and secure operation of the smart grid after a false injection attack, the tolerant intrusion control of the system after a false data injection attack is investigated. First, since there is no publicly available FDIA dataset, two datasets are generated: one contains random single-node attacks and the other contains random multi-node attacks. Second, combining AE and Generative Adversarial Network (GAN), and introducing Wasserstein distance and gradient penalty term to avoid the problems of gradient vanishing and pattern collapse that GAN is prone to in adversarial training;at the same time, adversarial training is used to achieve Nash equilibrium, learn spatial relationship between data, and complete the data reconstruction;the method does not need labeled data from measurement instruments, and only requires attack-free historical state data to complete the training, thus it is unsupervised learning. Finally, the simulation results show that the adopted recovery scheme can accurately restore the contaminated state quantities to their pre-attack values, and has high recovery accuracy for FDIA contamination. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Comprehensive State-of-the-Art of Vehicle-To-Grid Technology

Comprehensive State-of-the-Art of Vehicle-To-Grid Technology

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sciences and Techniques of automatic control and Computer engineering MI-STA, IEEE international Maghreb Meeting of the conference on

作者： Abdulgader Alsharif Abdussalam Ali Ahmed Mohamed Mohamed Khaleel Ahmed Salem Daw Alarga Omer. S. M. Jomah Ibrahim Imbayah Faculty of Engineering Universiti Teknologi Malaysia (UTM) Johor Bahru Malaysia Mechanical Engineering Department Bani Waleed University Bani Waleed Libya Department of Electrical-Electronics Engineering Karabuk University Karabuk Turkey Department of Computer Science Elmergib University Khums Libya Libyan Academy For Postgraduate Studies Tripoli Libya Department Energy Engineering College of Renewable Energy Tajoura Libya

A vehicle is a means of transportation, such as a car, truck, or train, that is capable of moving people or goods from one place to another. Vehicles can be classified based on various factors, such as the type of fuel they use (e.g. gasoline, diesel, electricity), the number of wheels they have (e.g. two, four, six), and their intended use (e.g. passenger transportation). Vehicles may have connectors, such as plug sockets or fuel ports, that allow them to be connected to other devices or systems to form Vehicle-to-Everything (V2X) technology. For example, an Electric Vehicle (EV) may have a charging port that allows it to be connected to an electric power source to recharge its batteries such Vehicle-to-Grid (V2G) as one of the V2X forms. One of the challenges in charging EVs is the availability of charging infrastructure. In many places, there are relatively few public charging stations, which can make it difficult for EV owners to find a place to charge their vehicles when they are away from home. Additionally, charging an electric vehicle can take significantly longer time than filling up a gasoline-powered vehicle, which can be inconvenient for some drivers. In this review, the various topologies of V2X, connectors, charging challenges, and EV impact types on the grid are conducted.

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