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IEEE PES Asia-Pacific Power and Energy engineering Conference (APPEEC)

作者： Wassanan Buasi Watcharin Srirattanawichaikul Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Graduate Program in Electrical Engineering Graduate School Chiang Mai University Chiang Mai Thailand Provincial Electricity Authority Bangkok Thailand

ISBN: (数字)9798350318098

ISBN: (纸本)9798350318104

This paper provides the power quality disturbances (PQDs) classification in distribution networks using an artificial neural network (ANN). Various forms of PQDs are considered, including sag, swell, harmonics, flickers, transients, sag with harmonics, and swell with harmonics. The simulation is divided into two parts. The first part is PQDs signals creation and feature extraction using discrete wavelet transform (DWT) and classification by using the dataset from the feature extraction step to be the input of artificial neural network (ANN). The second part is the model testing with the IEEE 9 bus test system with 5 PQDs, which is the most misclassified. The results of the proposed method will be demonstrated using simulation results in MATLAB/Simulink. The results show that the model can classify PQD signals into ten classes. The accuracy of the model is at 99.4%. After testing with the IEEE 9 bus test system, the total accuracy is at 95.6%.

关键词： Accuracy Power quality Artificial neural networks Distribution networks Feature extraction Harmonic analysis Mathematical models

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An arbitrarily reconfigurable extreme learning machine inference engine for robust ECG anomaly detection

IEEE Open Journal of Circuits and Systems

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IEEE Open Journal of Circuits and Systems 2021年 2卷 196-209页

作者： Chuang, Yu-Chuan Chen, Yi-Ta Li, Huai-Ting Wu, An-Yeu Andy Graduate Institute of Electronics Engineering National Taiwan University Taipei106 Taiwan Department of Electrical Engineering National Taiwan University Taipei106 Taiwan MediaTek Inc. Hsinchu30078 Taiwan

Extreme learning machine (ELM) has shown to be an effective and low-power approach for real-time electrocardiography (ECG) anomaly detection. However, prior ELM inference chips are noise-prone and lacking in reconfigurability. In this article, we present an arbitrarily reconfigurable ELM inference engine fabricated in 40-nm CMOS technology for robust ECG anomaly detection. By combining Adaptive boosting (Adaboost) and Eigenspace denoising with ELM (AE-ELM), robust classification under noisy conditions is achieved and saves the number of required multiplications by 95.9%. For chip implementation, a reconfigurable VLSI architecture is designed to support arbitrary complexity of AE-ELM, accounting for dynamic change in application requirements. On the other hand, we propose to construct the input weight matrix of ELM as a Bernoulli random matrix, which further reduces the number of multiplications by 55.2%. For real-time detection, parallel computing is exploited to reduce the latency by up to 86.8%. Overall, the 0.21-mm2 AE-ELM inference engine shows its robustness against noisy signals and achieves 1.83 × AEE compared with the state-of-the-art ELM design. © 2020 IEEE.

关键词： Electrocardiography

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Bringing Bearing Fault Detection to Embedded Systems Using Low-Cost Machine Learning Techniques

Bringing Bearing Fault Detection to Embedded Systems Using L...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： Natalia S. Teixeira M. A. Pastrana Henrique G. Moura Daniel M. Muñoz Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil Department of Mechanical Engineering Mechatronics Graduate Program University of Brasilia Brasilia DF Brazil Faculty of Gama Automotive Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

Vibration analysis is crucial for predictive maintenance of bearing systems, aiming to reduce costs and prevent failures. This paper investigates signal processing techniques such as FFTs and Hilbert Transforms for fault diagnosis, alongside decision tree models, particularly the J48 algorithm within the WEKA environment, for fault classification. The study emphasizes the integration of signal processing and machine learning for effective fault diagnosis and maintenance. Notably, a classification model with low computational cost has been chosen, facilitating implementation in embedded systems. This model also offers interpretability of outputs, as it is based on decision trees of frequency components obtained through preprocessing.

关键词： Vibrations Accuracy Computational modeling Transforms Machine learning Signal processing Robustness Mathematical models Field programmable gate arrays Predictive maintenance

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engineering dimensionality of collective dipole-dipole interactions using a nanophotonic environment

Engineering dimensionality of collective dipole-dipole inter...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Boddeti, Ashwin K. Wang, Yi Juarez, Xitlali Boltasseva, Alexandra Alaeian, Hadiseh Odom, Teri W. Jacob, Zubin Elmore Family School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Chemistry Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States

ISBN: (纸本)9781957171258

We experimentally demonstrate reduced dimensionality in a interacting ensemble of emitters. The well-known stretched exponential decay dynamics, (Equation presented) with β = 0.5 in 3D geometries, is strikingly modified in a nanophotonic environment that supports long-range interaction to β ~ 0.3. © Optica Publishing Group 2023.

关键词： Nanophotonics

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Organic-inorganic hybrid piezotronic bipolar junction transistor for pressure sensing

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Microsystems & Nanoengineering 2024年第3期10卷 229-244页

作者： Emad Iranmanesh Zihao Liang Weiwei Li Congwei Liao Shunyu Jin Chuan Liu Kai Wang Shengdong Zhang Charalampos Doumanidis Gehan A.J.Amaratunga Hang Zhou Guangdong Provincial Key Laboratory of In-Memory Computing Chips School of Electronic and Computer EngineeringPeking University Shenzhen Graduate SchoolShenzhen 518055P.R.China School of Mechanical Engineering Guangdong Technion-Israel Institute of TechnologyShantou 515063P.R.China State Key Laboratory of Microelectronics Device and Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029P.R.China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 23000PR China School of Electronics and Information Technology Sun Yat-sen UniversityNo.132 East Waihuan RoadGuangzhou 510006P.R.China Department of Mechanical Aerospaceand Biomedical EngineeringUniversity of South AlabamaShelby Hall3128MobileAL 36688USA Electrical Engineering Division Department of EngineeringUniversity of Cambridge9 JJ Thomson AvenueCambridge CB30FAUnited Kingdom Zhejiang University International CampusHainingChina

With the rapid development of the Internet of Things(IoTs),wearable sensors are playing an increasingly important role in daily monitoring of personal health and *** signal-to-noise-ratio has become the most critical performance factor to *** enhance it,on the one hand,good sensing materials/devices have been employed;on the other hand,signal amplification and noise reduction circuits have been ***,most of these devices and circuits work in an active sampling mode,requiring frequent data acquisition and hence,entailing high-power *** this scenario,a flexible and wearable event-triggered sensor with embedded signal amplification without an external power supply is of great ***,we report a flexible two-terminal piezotronic n-p-n bipolar junction transistor(PBJT)that acts as an autonomous and highly sensitive,current-and/or voltage-mediated pressure *** PBJT is formed by two back-to-back piezotronic diodes which are defined as emitter-base and collectorbase *** force exertion on the emitter side,as a result of the piezoelectric effect,the emitter-base diode is forward biased while the collector-base diode is reverse *** to the inherent BJT amplification effect,the PBJT achieves record-high sensitivities of 139.7 kPa^(-1)(current-based)and 88.66 kPa^(-1)(voltage-based)in sensing *** PBJT also has a fast response time of<110 ms under exertion of dynamic stimuli ranging from a flying butterfly to a gentle finger ***,the PBJT advances the state of the art not only in terms of sensitivity but also in regard to being self-driven and autonomous,making it promising for pressure sensing and other IoT applications.

关键词： bipolar transistor IoT

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Characterization of Thermally Driven V -shaped MEMS Actuator Using an Alternate Nonlinear RC Model

Characterization of Thermally Driven V -shaped MEMS Actuator...

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International Conference on Electric Power and Energy Conversion Systems (EPECS)

作者： Nidal A. Sherif Rached Dhaouadi Maher Bakri-Kassem Mechatronics Graduate Program American University of Sharjah Sharjah UAE Department of Electrical Engineering American University of Sharjah Sharjah UAE Department of Systems Design Engineering University of Waterloo Waterloo Canada

ISBN: (数字)9798331516963

ISBN: (纸本)9798331516970

This paper presents a reduced and efficient alternate model to simulate the nonlinear dynamics of a thermally driven V-shaped MEMS actuator. The experimental observation of the dynamic voltage-displacement relationship shows an overdamped response with a variable rise-time and fall-time indicating the simultaneous presence of complex energy storage and energy dissipation mechanisms. To completely characterize these mechanisms and yet have a simple representation for control, we develop an alternate model consisting of a set of ordinary nonlinear differential equations representing the behavior of a nonlinear RC circuit with variable parameters that are a function of the applied voltage. The simulation results show good agreement with the measured data and confirm the accuracy of the proposed alternate model.

关键词： Micromechanical devices Actuators Transient response Thermal variables control Energy dissipation Thermal variables measurement Mathematical models Integrated circuit modeling Voltage control Energy storage

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A PVT-Invariant Front-End Ring Amplifier using Self-Stabilization Technique for SAR ADC

A PVT-Invariant Front-End Ring Amplifier using Self-Stabiliz...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Chi-Wei Chen Chien-Yu Su Hsin-Shu Chen Graduate Institute of Electronics Engineering and Department of Electrical Engineering National Taiwan Univ

ISBN: (数字)9781665484855

ISBN: (纸本)9781665484862

This paper proposes a ring amplifier with a self-stabilization technique (SST) against PVT variation. It can significantly alleviate the risk of the instability issue, which is particularly problematic in the front-end design. This technique automatically adjusts the dead-zone voltage (${V}_{DZ}$) according to the output voltage ringing magnitude directly. With the technique, the ring amplifier can find a suitable dead-zone voltage with minimal accuracy degradation even in a wide PVT range without adding a complex control circuit or algorithm. This technique is applied on a ring amplifier with 10-bit SAR (Successive-Approximation) ADC, and both are implemented in the 40-nm CMOS process. According to the measurement results, 51.43 dB SNDR, 60.24 dB SFDR, and 8.25-bit at 500ksps are achieved while consuming 36$\mu$W.

关键词： Degradation Circuits and systems Logic gates CMOS process Circuit stability Registers Delays

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Local sampled-data gain-scheduling control of quasi-LPV systems 4th

Local sampled-data gain-scheduling control of quasi-LPV syst...

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4th IFAC Conference on Embedded Systems, Computational Intelligence and Telematics in Control CESCIT 2021

作者： Coutinho, Pedro H.S. Peixoto, Márcia L.C. Bernal, Miguel Nguyen, Anh-Tu Palhares, Reinaldo M. Federal University of Minas Gerais Graduate Program in Electrical Engineering Brazil Department of Electrical and Electronics Engineering Sonora Institute of Technology Mexico Université Polytechnique Hauts-de-France LAMIH UMR CNRS 8201 France Federal University of Minas Gerais Department of Electronics Engineering Brazil

This paper deals with the problem of sampled-data gain-scheduling control design for affine quasi-LPV systems. As the control implementation is based on sample-data and its update occurs only at specific sampling instants, the state-dependent scheduling functions of the controller are piecewise continuous. This characteristic causes a mismatch between the system model and the controller parameters, namely asynchronous scheduling functions of the controller with respect to the plant during the inter-sampling behavior. To cope with this phenomenon, a polytopic description of the inter-sampling is constructed based on bounding assumptions on the scheduling functions and their time derivatives. Then, regarding a time-delay approach, a constructive and numerically implementable LMI-based synthesis condition is derived, and a convex procedure is proposed for enlarging the estimate of the region of attraction of the origin of the closed-loop system. The time-derivative bounds of the scheduling functions are explicitly accounted into the local analysis to ensure the method's implementation. A numerical example is provided to illustrate the proposed methodology. Copyright © 2021 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： Controllers

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Near-Far Field Boundary Analysis and Transmit Covariance Optimization for Dual-Polarized XL-MIMO Communications

Near-Far Field Boundary Analysis and Transmit Covariance Opt...

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IEEE Conference on Wireless Communications and Networking

作者： Shuhao Zeng Boya Di Hongliang Zhang Zhu Han H. Vincent Poor School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen China Department of Electrical and Computer Engineering Princeton University USA School of Electronics Peking University Beijing China Electrical and Computer Engineering Department University of Houston USA Department of Computer Science and Engineering Kyung Hee University South Korea

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Extremely large-scale multiple-input multiple-output (XL-MIMO) is expected to play an important role in future sixth generation (6G) networks. Most existing works in this area focus on single-polarized XL-MIMO, where transceivers transmit and receive signals in only one polarization direction, leading to degraded data rates. To improve multiplexing performance, in this paper, we investigate downlink XL-MIMO networks with dual-polarized antennas. However, unlike conventional dual-polarized massive MIMO, the cross-polarization discrimination (XPD) of channels vary across base station antennas in dual-polarized XL-MIMO due to the enlarged antenna aperture, leading to following two challenges. First, conventional near-far field boundary is insufficient as it only accounts for phase differences across array elements while irrespective of XPD differences. Second, existing transmit covariance optimization methods developed for dual-polarized massive MIMO cannot be directly utilized, since they are developed based on uniform XPD and pathloss assumptions. To address these challenges, we model the variations of XPD across antennas, based on which a non-uniform XPD distance is introduced to complement existing near-far field boundary. Based on the new distance criterion, we propose an efficient scheme for optimizing the transmit covariance, which considers the non-uniform XPD and pathloss. Numerical results validate our analysis and demonstrate the effectiveness of the proposed algorithm.

关键词： 6G mobile communication Phased arrays Multiplexing Transmitting antennas Optimization methods Massive MIMO Downlink Aperture antennas Transceivers Numerical models

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Precision Agriculture Revolutionized: UAV-Based Detection of Leaffolders and Stem Borers in Ricefields using EfficientNetB1

Precision Agriculture Revolutionized: UAV-Based Detection of...

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Vrian Jay Ylaya Department of Electronics and Electrical Engineering-CEIT and PhEdD MIE-Graduate School Surigao del Norte State University Surigao City SDN Philippines

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

The need for efficient pest management in rice cultivation is crucial due to the significant damage caused by pests like leaffolders and stem borers. Conventional manual inspection and sensory detection methods are labor-intensive and often inaccurate, leading to delayed and ineffective pest control measures. This study developed a system that uses unmanned areal vehicle (UAV) and machine learning algorithms to track the leaffolder and stem borer in rice fields. This system allows farmers to track the leaffolder and stem borer effectively and reliably without physically inspecting their entire field to determine the percentage affected by leaffolder and stem borer in the ricefield. Results indicate varying degrees of performance across different machine learning algorithms, with Convolutional Neural Network (CNN), consistently demonstrating superior accuracy, notably achieving 90.89% accuracy with EfficientNetB1. SVMs also exhibit commendable performance, excelling in complex decision frontier description. Decision trees, random forests, and transfer learning present nuanced performance characteristics, each offering unique strengths and limitations. The developed system tracked the disease between 73.22% and 90.89% using five groups with five tests per group. This study demonstrates the system’s effectiveness and opens avenues for further research and application in other areas of precision agriculture.

关键词： Precision agriculture Accuracy Machine learning algorithms Transfer learning Transforms Autonomous aerial vehicles Classification algorithms Convolutional neural networks Reliability Residual neural networks

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