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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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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： Mahmoud Aly Mahmoud Shaaba Tamer Kasem Raafat Shalaby Mechatronics Program Nile University Giza Egypt Smart Engineering Systems Research Center (SESC) Nile University Giza Egypt

ISBN: (数字)9781837242863

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.

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Motion Measurement Methods for Nonlinear Analysis of Electrostatic MEMS Resonators 20

Motion Measurement Methods for Nonlinear Analysis of Electro...

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20th International Conference on Smart Technologies, EUROCON 2023

作者： Ghommem, Mehdi Alattar, Basil Lherbette, Michael Elhady, Alaaeldin Abdel-Rahman, Eihab American University of Sharjah Department of Mechanical Engineering Sharjah26666 United Arab Emirates Mechatronics Graduate Program American University of Sharjah Sharjah26666 United Arab Emirates SmarAct Metrology Rohdenweg Oldenburg Germany Systems Design Engineering University of Waterloo Waterloo Ontario Canada

ISBN: (纸本)9781665463973

In this paper, we compare two measurement techniques to analyze the dynamic response of a MEMS resonator, made of a microcantilever beam, that is electrostatically actuated via a side electrode. The first method is based on a combination of Michelson interferometry, knife-edge analysis, and stroboscopic imaging, and is used to dissect the in-plane and out-of-plane motions of the resonator. The second approach follows the motion-induced current method and is based on a transduction mechanism that converts the movement of the resonator to a current signal. The third harmonic of said current is directly related to the in-plane motion of the resonator. Motion-induced current measurements enable the detection of the nonlinear dynamics associated with the motion of the resonator when actuated with high excitation voltages. The optical and electrical measurements show similar nonlinear features in terms of the location of the cyclic-fold bifurcation in the parameter space and the hysteretic region associated with it. These dynamic features can be exploited for sensing purposes. © 2023 IEEE.

关键词： Interferometry

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Study on Offshore Wind Energy Potential in the Gulf of Thailand

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International Journal of Renewable Energy Research 2021年第4期11卷 1947-1958页

作者： Sawasklin, Pariyes Saeung, Somchai Taweekun, Juntakan Energy Technology Program Faculty of Engineering Prince of Songkla University Hat Yai Songkhla90112 Thailand Department of Mechanical and Mechatronics Engineering Faculty of Engineering Prince of Songkla University Hat Yai Songkhla90112 Thailand

Thailand's Alternative Energy Development Plan (AEDP) aims to reduce electric power generation from fossil fuels by generating electricity from wind. In this study, the purpsoe is to determine a good place for a wind farm installation. The wind potential of the Gulf of Thailand (GoT) was monitored every 10 minutes for four years (2017-2020) at 10 m agl of 10 meteorological masts and analyzed using the Wind Atlas Analysis and Application program (WAsP). Stations with average wind speeds greater than 3 m/s were provided to Multi Criteria Decision Analysis (MCDA) in order to find a viable offshore wind farm in GoT. Furthermore, the Annual Energy Product (AEP) was calculated and analyzed using 28 Vestas V112-3.0 MW Offshore in this study. The results revealed that Prachuap Khiri Khan and Narathiwat are two MCDA-selected stations. Prachuap Khiri Khan had a mean wind speed of 4.1 m/s and a power density of 121 W/m2, while Narathiwat had a mean wind speed of 4.5 m/s and a power density of 181 W/m2. Prachuap Khiri Khan's total net AEP was 226.7 GWh/year, with a capacity factor of 33.1%. Narathiwat's total net AEP was 270.8 GWh/year, with a capacity factor of 37%. In terms of economics, Narathiwat has a lower cost per unit than Prachuap Khiri Khan, at $0.14/kWh and $0.17 kWh, respectively. A suitable wind farm in the Gulf of Thailand allows wind energy to be used to generate electricity, which benefits the investor or people interested in offshore windfarm. © 2021. All Rights Reserved.

关键词： Fossil fuels

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Inpatient Monitoring System: Temperature, Oxygen Saturation, Blood Pressure, Heart Rate, and Infusion Automation Based on ESP 32, IoT, and Mobile Application

Inpatient Monitoring System: Temperature, Oxygen Saturation,...

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International Conference of Computer and Informatics engineering (IC2IE)

作者： Irvanda Joseph Patrick Anthony Winda Astuti Zener Sukra Lie Mahmud Iwan Solihin Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Department of Mechanical & Mechatronics Engineering UCSI University Kuala Lumpur Malaysia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

The implementation of a patient monitoring system and infusion automation which aims to ensure regular and periodic monitoring of inpatient conditions are applied in this system. This embedded system is applied in hospitals and addresses the uneven distribution of healthcare workers in Indonesia, particularly in remote areas. Currently, manual checks by nurses can lead to errors and reduced patient comfort. The improvement supervision is developed in this work. The system monitored body temperature, oxygen saturation, blood pressure, heart rate, and automated infusions. All the embedded systems are connected to Internet of Things (IoT) and a real-time database accessible through an application and web. This system allows doctors and hospital authorities to make decisions based on patient condition history. The testing phase of the system shows four data acquisition devices (temperature, oxygen saturation, blood pressure, and heart rate), an ESP 32, and Firebase as a database, have ability to capture and send real-time data every five seconds and can be accessed by doctors, patients, and hospital authorities.

关键词： Heart rate Temperature sensors Temperature measurement Automation Hospitals Databases Blood pressure Real-time systems Biomedical monitoring Testing

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Hardware Implementation of a Sliding Detection Algorithm for Robotic Hands Using Force Sensors

Hardware Implementation of a Sliding Detection Algorithm for...

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Symposium on Integrated Circuits and Systems Design (SBCCI)

作者： Jose Mendoza-Peñaloza Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Systems Graduate Program Automation and Control Group/GRACO Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

In this work, a sliding detection algorithm was proposed for a previously developed robotic hand through the utilization of force sensors. Previous works have designed several hardware architectures to filter sensor data, implement dynamic control, and machine learning models for controlling the robotic fingers using a single Field programmable Gate Arrays (FPGA) chip. In this regard, the slip detection algorithm was developed to comprise three stages, each with a low computational cost, including a moving average filter, a first-order derivative, and a peak detection algorithm. A reference model was constructed and validated through an experimental protocol employing daily use objects to create a database. Subsequently, the slip detection algorithm was mapped onto hardware utilizing previously developed floating-point arithmetic IP cores and implemented using a Zynq 7020 device. The FPGA implementation was characterized in terms of resource occupation, power consumption, execution time, and numerical error with the reference model.

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A Comparative Hardware Implementation of Histogram of Oriented Gradients as a Descriptor in Embedded Tracking of Swarm

SSRN

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SSRN 2023年

作者： Legarda, Diego Antonio Pérez, Karen Viviana Muñoz, Daniel Mauricio Department of Mechanical Engineering Mechatronics Systems Graduate Program University of Brasilia DF Brasilia70910-900 Brazil

The Histogram of Oriented Gradients (HOG) algorithm is widely utilized in image processing for tasks such as detection, classification, and tracking. However, several challenges arise when implementing this algorithm on computing platforms with limited memory and low power consumption, such as mobile robots and drones. This work presents an in-depth analysis and implementation of three innovative hardware architectures for HOG, specifically designed for real-time processing using Field programmable Gate Arrays (FPGAs) in the context of mobile robot localization. The primary focus of these architectures is to simplify the processing operations involved in gradient magnitude and orientation calculation, histogram generation, and normalization. These simplifications lead to a reduction in resource utilization and energy consumption. Experimental results conducted on a Zynq 7020 device demonstrated minimal relative error values throughout the en-Email addresseslegarda8027@*** (Diego Legarda), kperezlujan@*** (Karen Ṕerez), damuz@*** (Daniel M. Muñoz) 1Corresponding authorPreprint submitted to Journal of Parallel and Distributed Computing. July 31, 2023tire process, along with a significant execution time improvement of over 1000 times when compared to the software-based solution. © 2023, The Authors. All rights reserved.

关键词： Mobile robots

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An Intelligent Controller for an Assisted Electric Wheelchair based on Interval Type-2 Fuzzy Logic

An Intelligent Controller for an Assisted Electric Wheelchai...

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Advances in Science and engineering Technology International Conferences (ASET)

作者： Qutaiba A. H. Al-Bashayreh Ammar Kiftaro Mahmoud Alsheikh Mohammad A. Jaradat Mechatronics Engineering Gradute Program American University of Sharjah Sharjah UAE Mechanical Engineering Department American University of Sharjah Sharjah UAE

This paper proposes an intelligent controller design for an assisted electric wheelchair using interval type-2 fuzzy logic controller. The controller design has been structured using cascaded fuzzy inference system with feedback loop to avoid obstacles. In addition, to control the dynamics of the wheelchair, a speed fuzzy inference system has been added to the proposed controller. The controller is designed so that the user input is firstly obtained from the wheelchair joystick. The surrounding obstacles, thereafter, are detected using the input of three sensors attached to the wheelchair. At each time step, and until reaching the target point, the performed controller output generates both the motion angle and the wheelchair speed commands. The performance of the controller is tested by simulating the wheelchair travelling in different navigation scenarios. The simulation results confirm the effectiveness of the presented controller.

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Heading Angle Estimation Using Intelligent Fusion for Autonomous Vehicles

Heading Angle Estimation Using Intelligent Fusion for Autono...

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Advances in Science and engineering Technology International Conferences (ASET)

作者： Ali A. Barakat Mohammad A. Jardat Ahmed M. Elsergany Nidal A. Sherif Mechanical Engineering Department American University of Sharjah Sharjah UAE Mechatronics Engineering Graduate Program American University of Sharjah Sharjah UAE

Low-cost navigation systems for ground vehicles often rely on the fusion with Global Positioning System (GPS) for improved state estimation. In this study a low-cost gyroscope is fused with a GPS for improved vehicle heading angle estimation using several Artificial Intelligence (AI) based architectures that include Shallow Neural Networks (SNN), Multi-Layer Neural Networks (MLNN), and Adaptive Neuro- Fuzzy Inference Systems (ANFIS). The primary goal behind using AI based sensor fusion is to obtain a highly accurate vehicle heading estimation suitable for autonomous navigation applications. When available, the GPS signal is used to correct the vehicle's heading angle. The neural networks and ANFIS methods both use the difference between the GPS signal and the heading angle from the integrated gyroscope as inputs. The performance achieved is shown and analyzed. According to the results obtained, the MLNN provides the most accurate heading estimates.

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Intelligent Adaptive RRT* Path Planning Algorithm for Mobile Robots

Intelligent Adaptive RRT* Path Planning Algorithm for Mobile...

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Advances in Science and engineering Technology International Conferences (ASET)

作者： Omar Khattab Ahmed Yasser Mohammad A. Jaradat Lotfi Romdhane Mechatronics Engineering Graduate Program American University of Sharjah Sharjah UAE Mechanical Engineering Department American University of Sharjah Sharjah UAE

In this paper a new variant of the widely used Rapidly exploring Random Tree (RRT*) algorithm is proposed. The main goal of this variant is to improve the efficiency of the generated path, in both computation time and the quality of the path. In a previous work by the authors, an improved version RRT*N was proposed, where a normal probability distribution was used to control the generation of the random nodes. The proposed variant utilizes an intelligent fuzzy logic system (FLS) to control the generation of the random nodes and commands the robot to the required target introducing an intelligent fuzzy adaptive RRT*N path planning approach (FA-RRT*N). The proposed approach not only reduced the time required about 29.5 % of the time required by the RRT*, but also generally resulted in shorter path about 63% of the path generated by the traditional RRT * .

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