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11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Fawzy, Arwa Hassan, Ahmed Gad, Ahmed Zaky, Ahmed B. El-Hussieny, Haitham Alexandria Egypt program Alexandria Egypt Benha University Faculty of Engineering at Shoubra Electrical Engineering Department Egypt Egypt-Japan University of Science and Technology Department of Mechatronics and Robotics Engineering Alexandria Egypt

ISBN: (纸本)9798350369328

Pet owners experience difficulty in understanding their pets' body language and its implications for animal welfare, given that animals cannot utilize human speech to communicate their emotions and health conditions. However, previous experiments for analyzing cat behavior have demonstrated that cats are precisely expressive. DeepCat, a deep-learning approach developed in this study, translates cats' body language signals, enabling owners to discern their feline companions' intended messages and emotional states. Our DeepCat model was trained on a dataset comprising 10,000 cat images, implementing automatic labeling to track key features, including the tail, eyes, and mouth. Presented as a Flutter application, DeepCat can function everywhere, allowing owners to easily monitor their cats and make informed decisions in situations that require caution. This paper discusses the potential benefits and limitations of DeepCat and provides suggestions for future research in this domain. © 2023 IEEE.

关键词： Emotion Recognition

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WIND FARM SENSOR FAULT DIAGNOSIS USING ARTIFICIAL INTELLIGENCE AND WAVELET TRANSFORM

WIND FARM SENSOR FAULT DIAGNOSIS USING ARTIFICIAL INTELLIGEN...

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International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Aly, Mahmoud Shaaba, Mahmoud Kasem, Tamer Shalaby, Raafat Mechatronics Program Nile University Giza Egypt Nile University Giza Egypt Dept. of Engineering Mathematics and Physics Cairo University Giza Egypt Automatic Control Dept. Faculty of Electronic Engineering Menofia University Egypt

ISBN: (纸本)9781837242689

A methodology for the diagnosis of sensor faults in wind farms is introduced. Simulations are performed using a multi-domain model that integrates mechanical, electromagnetic, electronic control, and power grid components. The prevalent issue of intermittent sensor failures is addressed. The discrete wavelet transform is employed for feature extraction. The transient signals are processed effectively. Various wavelet families are evaluated to identify optimal candidates for fault diagnosis. Additionally, the methodology integrates three machine learning classifiers, achieving accuracy rates consistently exceeding 99%. The outcomes demonstrate the advantages of this approach in terms of enhanced accuracy. This research represents a significant advancement in sensor fault diagnosis, contributing valuable insights for the operation and maintenance of renewable energy systems. © The Institution of engineering & Technology 2024.

关键词： Windmill

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Application of Recurrence Plots and VGG Deep Learning Model to the Study of Condition Monitoring of Robotic Grinding

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International Journal of Precision engineering and Manufacturing 2023年第9期24卷 1675-1683页

作者： Chung, Kuan-Jung Dai, Cheng-Han Chiang, Tung-Chun Xie, June-Jia Lin, Ming-Tzer Department of Mechatronics Engineering National Changhua University of Education Changhua500 Taiwan Graduate Institute of Precision Engineering National Chung Hsing University Taichung402 Taiwan Doctoral Program in Industrial and Smart Technology Academy of Circular Economy National Chung Hsing University Nantou540 Taiwan

This study adopted AI to identify the normal and abnormal vibration signals generated during robotic grinding. This study classified four fundamental factors affecting grinding into three levels to obtain a widely used result and designed an L9(3 4) orthogonal array for the grinding experiment. During experimentation, part of the grinding wheels was added weight to produce abnormal vibration signals, which an accelerometer would measure. The study transformed the collected vibration signals into recurrence plots and conducted model training with VGG16 CNN architecture. Finally, this study tested a model with 89.6% training accuracy. The results showed the model could identify whether the recurrence plots stand for normal or abnormal vibrations, with an accuracy of 85%. This means it could predict normal and abnormal grinding conditions and help avoid problems caused by abnormal vibrations. © 2023, The Author(s), under exclusive licence to Korean Society for Precision engineering.

关键词： Grinding (machining)

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Applying CNN Models with Stereo Camera for Object Detection and Distance Estimation in Automatic Micro Electric Vehicle (MEVi) 1

Applying CNN Models with Stereo Camera for Object Detection ...

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1st International Conference on Smart mechatronics, ICSMech 2024

作者： Harimanto, Farrell Putra Hasanah, Nurul Pradana, Muhammad Khristamto Aditya Puji, Muhammad Nurul Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia National Research and Innovation Agency Kst Samaun Samadikun Research Center for Smart Mechatronics Bandung40135 Indonesia

ISBN: (纸本)9798350368918

Technological advancements in the automotive industry are currently focused on autonomous driving systems or driver assistance systems. Depth estimation is also an important feature of the autonomous driving system as it can accurately estimate the distance to the detected objects. In current developments technologies such as stereo cameras are more popular for a more accurate depth estimation. The process for object detection consists of a combination of classification, localization, and segmentation. Deep convolutional neural networks are the basis of object detection. The methods for object detection are divided into two categories namely the Region Proposal-based method such as RCNN, and the Classification-based method which provides for methods such as YOLO and MobileNet. As a part of the research conducted by the National Research and Innovation Agency (BRIN) on Automatic Micro Electric Vehicles or MEVi, this paper analyzed and compared the performance of several CNN models for object detection as well as the performance of depth sensing using ZED stereo camera which was used for the autonomous system in MEVi. Among several models that had been compared, YOLO v8 model demonstrates high accuracy and moderate speed as indicated by its high mAP (0.50) and FPS (38.46). Based on depth sensing results, the accuracy of distance measurement also depended on brightness and environment with the average of accuracy achieved indoors was 98.2% and outdoors was 96.3%. © 2024 IEEE.

关键词： Automotive industry

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High-Performance Chip Design With Parallel Architecture for Magnetic Field Imaging System

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IEEE Transactions on Instrumentation and Measurement 2024年 73卷 1-13页

作者： Lin, Ming-Yi Hsieh, Sheng-Hsien Chen, Ching-Han Lin, Chun-Hung Yuan Ze University Department of Computer Science and Engineering Taoyuan320315 Taiwan National Pingtung University of Science and Technology Program of Artificial Intelligence and Mechatronics Pingtung912301 Taiwan National Central University Department of Computer Science and Information Engineering Taoyuan32001 Taiwan International Games System Company Ltd. New Taipei City248 Taiwan

To address the limitations of typical coil detection systems and enhance the performance of traditional magnetic field imaging (MFI) systems, we propose a MFI system that uses a 4×4 array of anisotropic magnetoresistance (AMR) sensors. The core controller of the proposed system was designed using a pipelined parallelization algorithm and implemented on a high-speed field-programmable gate array (FPGA) in a fully hardware-based architecture. The designed MFI system can achieve parallel acquisition of magnetic field components from the 16-channel AMR sensor array, parallel data processing, parallel data transmission, and parallel computations in a single cycle of only 4 ms. Compared with typical detection systems, the proposed solution not only exhibits superior performance but can also provide dynamic visual representations of sensed information. © 1963-2012 IEEE.

关键词： Parallel architectures

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Implementation of a PID Controller using Online Tuning Applied to a Mobile Robot Obstacle Following/Avoidance

Implementation of a PID Controller using Online Tuning Appli...

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Argentine Conference on Electronics (CAE)

作者： M. A. Pastrana L. H. Oliveira D. A. Mendes Douglas. L. Silva Jose Mendoza-Peñaloza Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Graduate Program Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

The implementation of a bioinspired PID-based controller with online tuning capabilities is developed for obstacle following/avoidance of a nonholonomic mobile robot. An innovative mixture of the conventional PID controller and particle swarm optimization (PSO), which has a strong capability of adaptation across unknown scenarios, reduced objective error, brings us a novel online tuning methodology that can derive optimal controller parameters for a given scenario. It is appropriate for a kind of plant without prior knowledge or established mobile robot model. Computer simulation for obstacle following/avoidance is carried out in four different scenarios using the CoppeliaSim software and the EVA mobile robot platform. The effectiveness of the proposed control algorithm is demonstrated trough the simulation experiment, which shows its superior performance in the training scenario, including an overshoot of 20.1 %, a settling time of 10 seconds, and a steady-state error of 0.76%.

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Applying ant colony optimization algorithm to solve flying probe inspection problem

Applying ant colony optimization algorithm to solve flying p...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Chen, Chih-Yung Chang, Yu-Ming National Pingtung University of Science and Technology Program in Artificial Intelligence and Mechatronics Pingtung Taiwan Shu-Te University Department of Computer Science and Information Engineering Kaohsiung Taiwan

ISBN: (纸本)9798350324174

This paper applies ant colony optimization (ACO) algorithm for the dual-pin flying probe circuit board inspection optimal path searching problem. First, the proposed approach creates a representation for circuit inspection path, which groups and encodes the measurement endpoints into a sequence. Moreover, the ant colony algorithm with the sequence can be used to solve the complex circuit optimal problem. The experimental results show that the best solutions of ACO are performed better than other algorithms. © 2023 IEEE.

关键词： Inspection

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Design and Performance Comparison of Current References for a 32-bit Microcontroller Using 22nm Technology 16

Design and Performance Comparison of Current References for ...

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16th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2025

作者： Barcelos, Eduardo A. Campagnucci, Pamela R. A. N. Munoz, Daniel M. Amaral, Wellington A. Haddad, Sandro A. P. Mechatronics Graduate Program Faculty of Technology Department of Mechanical Engineering Electronics Engineering Undergraduate Program University of Brasilia Faculty of Gama DF Brasilia Brazil

ISBN: (纸本)9798331522124

With the advancement of semiconductor technologies, the need for efficient power management solutions in integrated systems, such as RISC-V architecture-based microcontrollers, becomes increasingly critical. However, there is a lack of studies comparing current reference architectures in terms of performance and robustness, particularly in 22nm technologies. In this paper, we present a comparative analysis of two current reference designs implemented in the same technology-referred to as Reference Design A and Reference Design B. We focus on their approaches to thermal compensation, supply stability, and layout optimizations. Through simulations and experimental tests, we evaluate the performance of each design within a power management system that includes DC-DC converters and LDO regulators. Our results indicate that Design A exhibits superior power supply rejection with a PSRR of -85 dB, while Design B demonstrates enhanced energy efficiency and thermal stability, achieving a nominal current of 5.14 μA and a temperature coefficient of 16.21 ppm. These findings underscore the importance of balancing energy efficiency, thermal stability, and power supply variation rejection when selecting current references for low-power, high-reliability applications, such as those in the Internet of Things (IoT). © 2025 IEEE.

关键词： Integrated circuit layout

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The Design of a Drone-Assisted System for Large Wildlife Vaccination Shooting Based on AI Image Identification Technology 20

The Design of a Drone-Assisted System for Large Wildlife Vac...

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20th IEEE International Conference on e-Business engineering, ICEBE 2024

作者： Tsai, Yao-Yu Tsai, Yao-Chuan Tai, Chang-Hsien Chen, Chen-Chih Hsu, Uzu-Kuei National Chung Hsing University National Pingtung University of Science and Technology Sustainable Circular Economy R&d Center Department of Bio-Industrial Mechatronics Engineering Pingtung Taichung Taiwan National Chung Hsing University Department of Bio-Industrial Mechatronics Engineering Taichung Taiwan College of Biomedical Engineering and Technology Tzu Chi University Hualien Taiwan Institute of Wildlife Conservation National Pingtung University of Science and Technology Pingtung Taiwan Program of Artificial Intelligence and Mechatronics National Pingtung University of Science and Technology Pingtung Taiwan

ISBN: (纸本)9798350365856

This study designs a UAV -assisted system integrated with AI image recognition technology to alleviate the difficulty for operators in stabilizing the UAV and accurately administering vaccines. The system uses thermal imaging modules and AI recognition systems to lock onto and track target animals in real-time. Utilizing MAVLink, the UAV adjusts its flight path based on the dynamic behavior of the animals, ensuring that the target remains within shooting range for precise vaccine administration. This technology not only improves the efficiency and accuracy of wildlife vaccination but also significantly reduces the workload on operators, providing a forward-looking solution for wildlife management. © 2024 IEEE.

关键词： Thermography (imaging)

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Design and Performance Comparison of Current References for a 32-bit Microcontroller Using 22nm Technology

Design and Performance Comparison of Current References for ...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Eduardo A. Barcelos Pâmela R. A. N. Campagnucci Daniel M. Muñoz Wellington A. Amaral Sandro A. P. Haddad Department of Mechanical Engineering Faculty of Technology Mechatronics Graduate Program Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

关键词： Resistance Microcontrollers Power system management Stability criteria Energy efficiency Robustness Circuit stability Thermal analysis Internet of Things Thermal stability

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