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21st Polish control Conference, PCC 2023

作者： Oprzedkiewicz, Krzysztof Rosol, Maciej Mitkowski, Wojciech Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatic Control Informatics and Biomedical Engineering AGH University of Science and Technology al. A Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031351693

In the paper the problem of modeling of thermal processes in microcontroller system is addressed. The proposed models allow to describe thermal processes during work of an evaluation system. The temperature in critical places of the system is measured using thermal camera. The proposed models have the form of hybrid transfer functions, containing both Integer Order (IO) and Fractional Order (FO) parts. The step responses of the proposed transfer functions are computed analytically. Results of experiments show that the proposed models are more accurate in the sense of Mean Square Error (MSE) cost function than typical transfer function models with delay. The proposed models can be applied to predict of overheating of microcotroller systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Microcontrollers

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Numerical Estimation of the Internal Positivity of the Fractional Order Model of a Two-Dimensional Heat Transfer Process 27th

Numerical Estimation of the Internal Positivity of the F...

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27th International Conference on Automation, AUTOMATION 2023

作者： Oprzędkiewicz, Krzysztof Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatic Control Informatics and Biomedical Engineering AGH University of Science and Technology al. A Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031258435

In the paper the numerical estimation of the internal positivity of the model of a two dimensional heat transfer process is addressed. The considered thermal process is described by the fractional order state equation, derived from parabolic heat equation with homogenous Neumann boundary conditions and distributed control and observation. Two numerical algorithms of the positivity testing are proposed and compared. The first one consists in the full examination of the whole area. The next one uses Monte Carlo method. From tests it can be concluded that the considered model can be internally positive only for its lower orders and heating and measurements located closely to the corner of the tested area. The use of the Monte Carlo method allows to significantly shorten the duration of computations. The presented results can be useful in measurements using a thermal camera. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fractional order system Monte Carlo method Positivity Thermal camera

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Design of bifunctional composite bone age prediction network based on Swin-Transformer

Design of bifunctional composite bone age prediction network...

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2024 International Conference on Intelligent Manufacturing and Mechatronics, IMM 2024

作者： Zhiling, Qian Yuhao, Yuan Department of Engineering and Control Science Nanjing University of Technology Nanjing210000 China Department of Vision and Robotics Centre Universitaire Condorcet Université de Bourgogne Le Creusot71200 France

Bone age can be predicted by taking hand X-rays. Prediction of bone age is a labor-intensive and time-consuming radiological clinical task. This paper combined a series of prevailing deep learning methods to address this problem. Stages1~3 of Swin Transformer served as backbone, with the multi-scale neck network and detection head of Yolox connected to it. These formed the first period’s hand bone joints detector. After finishing detector training, the pre-trained Stages1~3 were frozen for the second period’s developmental grades classification of corresponding bone joint. Additionally, a linear classification head was attached to Swin Transformer’s stage4, where it functioned as second period’s classifier for different developmental grades. Therefore, a dual-purpose composite network was created like this. It made the bone age prediction model have high integrated level, and the two periods could be applied fusion training. In addition, different attention mechanisms were introduced at different positions, loss functions and optimization methods were also redesigned to ensure improvement of network performance. In the hand bone joints detection period, compared to the original Yolox-X, there was a 5.27% increase in Ap@50 and a 40.12% increase in Ap@50:95. As for the developmental grade classification period, the validation accuracy surpassed that of EfficientNetV2-L by 5.18%, with one-third the training size. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Deep learning

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Fault Detection in Electric Drives Based on LSTM Autoencoder Model Machine Learning Approach 25

Fault Detection in Electric Drives Based on LSTM Autoencoder...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Demidova, Galina Privalov, Daniil Semenov, Denis Lukichev, Dmitry Liu, Zhitao Anuchin, Alecksey Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Department of Electric Drives Moscow Power Engineering Institute Moscow Russia

ISBN: (纸本)9798350389234

Fault detection in electric drives is crucial for ensuring operational reliability and minimizing downtime. This paper provides a brief overview of the methods based on machine learning used for fault detection in electric drives. Additional this research presents a machine learning approach that utilizes the Long Short-Term Memory Autoencoder model for fault detection deal with bearing faults. A flowchart illustrating the implementation steps of the Long Short-Term Memory Autoencoder algorithm is included. Additionally, a case study on bearing faults in an electric drive system is presented to demonstrate the advantage of the proposed approach. By training the Long Short-Term Memory Autoencoder on operational data, accurate prediction of bearing faults is achieved, enabling timely maintenance interventions. It is shown that in the 7th epoch of training, the model achieved a notably high accuracy more than 99%. The results highlight the potential of Long Short-Term Memory Autoencoder models as a valuable tool for fault detection in electric drives, thereby improving system reliability and performance. © 2024 IEEE.

关键词： Machine learning

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MATERIAL, TORQUE, AND STRUCTURAL STUDY OF A FOLDABLE ROBOTIC ARM FOR AERIAL DRONES

MATERIAL, TORQUE, AND STRUCTURAL STUDY OF A FOLDABLE ROBOTIC...

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ASME 2024 International Mechanical engineering Congress and Exposition, IMECE 2024

作者： Bingham, Kyler Zakrevski, Christopher Deemyad, Taher Department of Mechanical and Measurement & Control Engineering Idaho State University PocatelloID United States Department of Robotics and Communication Systems Idaho State University PocatelloID United States

ISBN: (纸本)9780791888681

The paper discusses the integration of foldable robotic arms into unmanned aerial vehicles (UAVs), particularly focusing on their application in precision agriculture for fruit picking. The design process, from conceptualization to 3D modeling, ensures the arm's functionality while minimizing interference with the drone's flight dynamics. Material selection, emphasizing the balance between strength and weight, favors Onyx, a nylon blend reinforced with carbon fiber, and the honeycomb infill pattern for its exceptional mechanical properties. Torque analysis confirms the arm's manageable impact on UAV stability. The research underscores the potential of foldable robotic arms to enhance UAV capabilities in various tasks, offering insights into their broader applicability beyond agriculture. It contributes to UAV design and robotics by addressing challenges in integrating functional accessories, emphasizing the importance of material selection and structural design in optimizing UAV performance. © 2024 by ASME.

关键词： Drones

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A piezoresistive-based 3-axial MEMS tactile sensor and integrated surgical forceps for gastrointestinal endoscopic minimally invasive surgery

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Microsystems & Nanoengineering 2024年第5期10卷 71-83页

作者： Cheng Hou Huxin Gao Xiaoxiao Yang Guangming Xue Xiuli Zuo Yanqing Li Dongsheng Li Bo Lu Hongliang Ren Huicong Liu Lining Sun School of Mechanical and Electrical Engineering Jiangsu Provincial Key Laboratory of Advanced RoboticsSoochow UniversitySuzhouChina Faculty of Mechanical and Electrical Engineering Kunming University of Science and TechnologyJingming South RoadKunmingChina Yunnan Key Laboratory of Intelligent Control and Application KunmingChina Department of Electronic Engineering The Chinese University of Hong Kong(CUHK)Hong KongChina. Department of Gastroenterology Qilu HospitalShandong UniversityJinanShandongChina

In robotic-assisted surgery(RAS),traditional surgical instruments without sensing capability cannot perceive accurate operational forces during the task,and such drawbacks can be largely intensified when sophisticated tasks involving flexible and slender arms with small end-effectors,such as in gastrointestinal endoscopic surgery(GES).In this study,we propose a microelectromechanical system(MEMS)piezoresistive 3-axial tactile sensor for GES forceps,which can intuitively provide surgeons with online force feedback during robotic *** MEMS fabrication process facilitates sensor chips with miniaturized *** fully encapsulated tactile sensors can be effortlessly integrated into miniature GES forceps,which feature a slender diameter of just 3.5 mm and undergo meticulous calibration procedures via the least squares *** experiments,the sensor's ability to accurately measure directional forces up to 1.2 N in the Z axis was validated,demonstrating an average relative error of only 1.18%compared with the full-scale *** results indicate that this tactile sensor can provide effective 3-axial force sensing during surgical operations,such as grasping and pulling,and in ex vivo testing with a porcine *** compact size,high precision,and integrability of the sensor establish solid foundations for clinical application in the operating theater.

关键词： axial surgery intensified

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Application of Statistical Methods to Support Automation of Pricing in Business 21st

Application of Statistical Methods to Support Automation o...

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21st Polish control Conference, PCC 2023

作者： Grobler-Debska, Katarzyna Kucharska, Edyta Mularczyk, Rafal Jagodziński, Mieczyslaw Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland Department of Systems Biology and Engineering Silesian University of Technology Gliwice Poland

ISBN: (纸本)9783031351723

This paper presents the possibility of using statistical modeling to automate the process of dynamic pricing management with revenue control and adaptation to current legislation in this area. In addition, it is proposed the use of integration of Python tools with the ERP and BI systems popularly used in the industry. This integration in order to facilitates decision-making in this area for the business without the end of programming. The proposed solutions support the CEO enterprises make decisions regarding pricing strategies and optimize their revenues. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Lidar-Visual-Inertial Odometry with Online Extrinsic Calibration

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Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 70-76页

作者：茅天阳赵文韬王景川陈卫东 Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China

To achieve precise localization,autonomous vehicles usually rely on a multi-sensor perception system surrounding the mobile *** is a time-consuming process,and mechanical distortion will cause extrinsic calibration ***,we propose a lidar-visual-inertial odometry,which is combined with an adapted sliding window mechanism and allows for online nonlinear optimization and extrinsic *** the adapted sliding window mechanism,spatial-temporal alignment is performed to manage measurements arriving at different *** nonlinear optimization with online calibration,visual features,cloud features,and inertial measurement unit(IMU)measurements are used to estimate the ego-motion and perform extrinsic *** experiments were carried out on both public datasets and real-world *** indicate that the proposed system outperforms state-of-the-art open-source methods when facing challenging sensor-degenerating conditions.

关键词： autonomous vehicles multi-sensor fusion online calibration

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Influence of Histogram Equalization on Multi-Classification of Retinal Diseases in OCT B-scans

Influence of Histogram Equalization on Multi-Classification ...

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Tomasz Marciniak Agnieszka Stankiewicz Department of Automatic Control Robotics and Electrical Engineering Institue of Automatic Control and Robotics Poznan University of Technology Poznan Poland

ISBN: (数字)9788362065486

ISBN: (纸本)9798350373806

The aim of this article is to analyze the impact of adaptive histogram equalization of the human eye OCT B-scans on the effectiveness of the classification of pathological changes. Tests were performed on two datasets. The first dataset contains 4 class B-scans (CNV, DME, DRUSEN, and NORMAL) taken with the use of Spectralis Heidelberg device, while the second dataset contains images from two devices (Spectralis Heidelberg OCT and Avanti Optovue OCT) and additionally contains the VMT (i.e., vitreomacular traction) class. The images were subjected to standard histogram equalization and contrast limited adaptive histogram equalization (CLAHE) with various parameters. The classification process was carried out using VGG16 artificial neural network. It can be observed that histogram equalization has no significant impact on improving classification performance.

关键词： Performance evaluation Histograms Pathology Optical coherence tomography Signal processing algorithms Artificial neural networks Adaptive equalizers Retina Standards Diseases

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The Development of a Lithium-Ion Battery Analyzer for Data-Driven Analysis of Battery Performance

The Development of a Lithium-Ion Battery Analyzer for Data-D...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Jaitrong, Kunanon Seetisarn, Puvit Numsomran, Arjin Tipsuwanporn, Vittaya Chaoraingern, Jutarut School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Instrumentation and Control Engineering Bangkok Thailand Ruamrudee International School Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Robotics and Ai Engineering Bangkok Thailand

ISBN: (纸本)9798350350821

As demand for higher energy density, faster charging, and longer lifespan increases, so too does the need for sophisticated analysis of battery performance. This study focuses on the development of a lithium-ion battery analyzer for data-driven battery performance analysis. The system comprises a hardware platform and a cloud-connected software infrastructure. The hardware utilizes an STM32 microcontroller integrated with an LTC6803 for precise battery parameter measurements, including voltage, current, and temperature. The charging circuit is an LTC-4162, allowing for controlled charging profiles. A Raspberry Pi, running Raspbian OS, acts as the central processing unit, collecting data from the microcontroller and displaying it on a user-friendly human machine interface developed using Node-RED. Crucially, the system leverages cloud connectivity for data storage, analysis, and remote monitoring. The system transmits measured data to a cloud platform, which offers scalable storage and facilitates the development of sophisticated data analysis algorithms. This cloud integration allows for real-time battery performance monitoring and visualization through a dedicated application. Additionally, the system incorporates a local data backup mechanism, ensuring data accessibility even during internet disruptions. The developed system provides a comprehensive platform for data-driven insights into battery health, enabling informed decisions regarding battery operation and maintenance. © 2024 IEEE.

关键词： Microcontrollers

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