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Measurement of surface stress-strain distribution inside a grain of carbon steel via optical microscope

Measurement: Journal of the International Measurement Confederation 2025年 255卷

作者： Dharmawan, I Dewa Made Oka Lee, Jinyi Department of Control Instrumentation and Robot Engineering of Chosun University Gwangju61452 Cuba Interdisciplinary Program in IT-BIO Convergence System Chosun University Gwangju61452 Cuba Department of Electronic Engineering Chosun University Gwangju61452 Cuba

The advancement of alloys and steel in engineering highlights the critical need for robust methods to ensure structural integrity. While traditional Non-Destructive Testing and Evaluation (NDT/E) techniques provide valuable insights, they often fail to detect pre-existing stress conditions that contribute to fatigue cracks. Recent approaches have addressed this limitation by analyzing stress and strain at the grain level using advanced measurement systems—often based on diffraction techniques—integrated with Finite Element Method (FEM) and Digital Image Correlation (DIC) platforms. However, the application of these techniques for in-service inspections remains limited by challenges in accessibility, cost, and scalability. To overcome these issues, an integrated 2D surface system combining optical microscopy with DIC and grain-level analysis within the FEM framework is proposed. This method enables efficient visualization of grain-level deformation and stress distribution, thereby providing deeper insights into the microstructural behavior of polycrystalline materials under external loads. The proposed methodology is theoretically outlined and validated through simulations and experimental analyses, demonstrating its potential as a practical solution for in-service inspections. Ultimately, this approach is expected to advance inspection techniques by offering an accessible and scalable tool for monitoring microstructural behavior and identifying potential failure mechanisms through surface analysis. © 2025 Elsevier Ltd

关键词： Polycrystalline materials

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Continuous Perception Garment Classification Based on Optical Flow Variation

Continuous Perception Garment Classification Based on Optica...

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IEEE International Conference on Robotics and Biomimetics

作者： Li Huang Tong Yang Yu Zhang Rongxin Jiang- Xiang Tian Yaowu Chen Institute of Advanced Digital Technologies and Instrumentation Zhejiang University Hangzhou China State Key Laboratory of Industrial Control and Technology Zhejiang University China Zhejiang Provincial Key Laboratory for Network Multimedia Technology Hangzhou China Ministry of Education of China Embedded System Engineering Research Center Hangzhou China

ISBN: (纸本)9781665481106

A novel continuous perception garment classification mechanism is proposed in this paper, with the aim to identify the correct category of the garment from a set of known categories. It has been observed that due to the severe folding and overlapped texture of garments, treating a video of the continuous deformation of cloth as a set of disordered static figures would be ineffective which leads to low classification precision performed by an image-based garment classifier. In contrast, a high-level decision making module that leverages the classification results of each single image would significantly increase the algorithm performance. In this paper, we incorporate the optical flow variation of deformable cloth between consecutive configurations as a representative of how it is traversing within the confidence interval of the image-based classifier. We claim that it is not the number of video frames but the sum of optical flow variation of the garment configuration between consecutive frames having the same category label that constitutes the belief of garment classification. In other words, if two consecutive visual appearances of the garment could be identified as the same category by the image-based classifier, then the more diverged that two configurations are, the more confident that the garment is correctly identified. Experimental comparisons between the state-of-the-art algorithm and the proposed algorithm in a public dataset have been provided which prove the validity of the proposed algorithm.

关键词： Visualization Biomimetics Clothing Decision making Robot sensing systems Classification algorithms Task analysis

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Comparison of Magneto-Optical Faraday Effect Method and Magnetic Camera for Imaging the 2-D Static Leakage Magnetic Flux Density

e-Journal of Nondestructive Testing

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e-Journal of Nondestructive Testing 2022年第9期27卷

作者： Dharmawan, I Dewa Made Oka Lee, Jinyi Wang, Dabin Department of Control Instrumentation and Robot Engineering Chosun University Gwangju61452 Korea Republic of Interdisciplinary Program in IT-BIO Convergence System Chosun University Gwangju61452 Korea Republic of Department of Electronic Engineering Chosun University Gwangju61452 Korea Republic of IT-Based Real-Time NDT Center Chosun University Gwangju61452 Korea Republic of

Recent development of electromagnetic inspection proposed auspicious results for imaging 2-D static of leakage magnetic flux density (LMFD) on surface and sub-surface defects. This ability encourages an interest in implementing electromagnetic-based magnetic flux leakage (MFL) testing for nondestructive inspection (NDI). In recent NDI technologies, advanced magnetic inspection using magneto-optical Faraday effect (MOE) and magnetic camera dominated the pre-service and in-service inspection in critical engineering industries such as aerospace, steel manufacturing, marine, railroad, and nuclear facilities. Unfortunately, a compact comparison of these approaches has not been proposed yet. This study aimed to compare MOE and magnetic camera according to five primary analyses: the target object, magnetic source, configuration of the magnetic sensor, signal processing, and AI implementation. A literature study was conducted using 47 papers to analyze the performance of each device in capturing LMFD. This comparison study successfully obtained the advantages and limitations of each imaging technique, which is very beneficial as a compact reference for developing and selecting suitable nondestructive inspection devices for MFL testing in the future. In addition, artificial intelligence (AI) as an option to escalate the inspection confidence could increase the assessment efficiency and reliability considering fast and complex engineering systems. © 2022, NDT. net GmbH and Co. KG. All rights reserved.

关键词： Nondestructive examination

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基于自解耦三明治结构的横向运动栅场效应晶体管MEMS微力传感器

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engineering 2023年第2期21卷 61-74,M0004页

作者：高文迪乔智霞韩香广王小章 Adnan Shakoor 刘存朗卢德江杨萍赵立波王永录王久洪蒋庄德孙东 State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesOverseas Expertise Introduction Center for Micro/Nano Manufacturing and Nano Measurement Technologies Discipline InnovationXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemSchool of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150006China Eleventh Research Institute Sixth Academy of China Aerospace Science and Technology Co.Xi’an 710100China Department of Control and Instrumentation Engineering King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Department of Biomedical Engineering City University of Hong KongHong Kong 999077China

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵... 详细信息

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵列层和两个软光阻层SU-8组成。通过所提出的双差分传感结构,LMGFET横向工作在垂直干扰下的输出电流被大大消除,所提出传感器的相对输出误差从4.53%(传统差分结构)降低到0.01%。提出了一种实用的传感器制造工艺,并对其进行了模拟。基于LMGFET的力传感器的灵敏度为4.65μA·nN^(-1),可与垂直可移动栅极场效应晶体管(VMGFET)器件相媲美,但非线性度提高了0.78%,测量范围扩大了±5.10μN。这些分析为LMGFET器件的电气和结构参数提供了全面的设计优化,并证明了所提出的传感器在生物医学显微操作应用中具有良好的力传感潜力。

关键词：力传感器场效应晶体管横向运动三明治结构电气模型显微操作非线性度双差分

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High-Performance Nonlinear control for Three-Phase Two-Level Boost PFC Rectifier

High-Performance Nonlinear Control for Three-Phase Two-Level...

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Materials and Energy: Energy in Electrical engineering (ICOME-EE), International Conference on

作者： Songklod Sriprang Babak Nahid-Mobarakeh Noureddine Takorabet Serge Pierfederici Apinya Siangsanoh Kanapot Yodmanee Pongsiri Mungporn Phatiphat Thounthong Nitchamon Poonnoy Nicu Bizon Thong-In Suyata Sakrit Noosawang GREEN-ENSEM Laboratory Université de Lorraine France Rattanakosin Wang Klai Kangwon Campus Petchkasem RD Rajamangala University of Technology Prachuap Khiri Khan Thailand LEMTA Laboratory Université de Lorraine France Renewable Energy Research Centre (RERC) Thai-French Innovation Institute King Mongkut’s University of Technology North Bangkok Bangkok Thailand Dept. Teacher Training in Electrical Engineering Faculty of Technical Education Faculty of Electronics Communication and Computers University of Pitesti Pitesti Romania Department of Electrical Engineering Faculty of Rajamangala University of Technology Thailand Dept. of Control System and Instrumentation Engineering Faculty of Engineering King Mongkut’s University of Technology Thonburi Bangkok Thailand

ISBN: (数字)9798331531577

ISBN: (纸本)9798331531584

This paper presents a high-performance nonlinear control strategy for a three-phase, two-level boost Power Factor Correction (PFC) rectifier. The proposed control method aims to achieve superior performance in terms of power factor correction, output voltage regulation, and dynamic response under various operating conditions. Utilizing advanced nonlinear control techniques, the system ensures optimal tracking of the reference signals, minimizing total harmonic distortion (THD) and improving overall efficiency. The effectiveness of the control strategy is validated through extensive simulations and experimental results, demonstrating significant improvements in the transient and steady-state performance of the rectifier. This approach provides a robust and efficient solution for PFC applications in modern power electronics systems.

关键词： Electrical engineering Dynamic response Total harmonic distortion Rectifiers Power factor correction control systems Power electronics Steady-state Voltage control Transient analysis

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Fault diagnosis for PV arrays considering dust impact based on transformed graphical features of characteristic curves and convolutional neural network with CBAM modules

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Applied Energy 2024年 355卷

作者： Jiaqi Qu Qiang Sun Zheng Qian Lu Wei Hamidreza Zareipour School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing China School of Electronics and Information Engineering Beihang University Beijing China The Department of Electrical and Computer Engineering University of Calgary Calgary Canada

Various faults can occur during the operation of photovoltaic (PV) arrays, and both dust-affected operating conditions and various diode configurations complicate the faults. However, current methods for fault diagnosis based on I-V characteristic curves usually do not effectively use all the distinguishable information contained in the I-V curves or often rely on calibrating the field characteristic curves to standard test conditions (STC). It is difficult to apply these methods in practice and accurately identify multiple complex faults with similarities in different blocking diode configurations of PV arrays under the influence of dust. Therefore, a novel fault-diagnosis method for PV arrays that considers the impact of dust is proposed. In the pre-processing stage, the Isc-Voc normalized Gramian angular difference field (GADF) method is presented, which normalizes and transforms the resampled PV array characteristic curves from the field, including I-V and P-V, to obtain transformed graphical feature matrices. Subsequently, in the fault diagnosis stage, the convolutional neural network (CNN) model with convolutional block attention modules (CBAM) is designed to classify faults, which identifies complex fault types from the transformed graphical matrices containing complete discriminative fault information. In addition, the performances of different graphical feature transformation and CNN-based classification methods are compared using case studies. The results indicate that the developed method for PV arrays with different blocking diode configurations under various operating conditions has high fault diagnosis accuracy and reliability.

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Fault Tolerant Localization Based on K-means Clustering in Wireless Sensor Networks

Fault Tolerant Localization Based on K-means Clustering in W...

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IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： Soumya J Bhat K V Santhosh Department of Instrumentation and Control Engineering Centre for Cyber Physical System Manipal Institute of Technology Manipal Academy of Higher Education (MAHE) Manipal India

ISBN: (数字)9781728168289

ISBN: (纸本)9781728168296

Wireless Sensor Network (WSN) has been considered as an essential tool for many applications. Most of the applications of WSNs require the location of sensor nodes to be known. But, because of high power consumption and cost, it is not suitable to attach a GPS receiver with every node. For estimating the location of sensor nodes, localization algorithms make use of few location-aware nodes as reference nodes. But, sometimes, these reference nodes can turn faulty. They may estimate their locations wrongly due to software or hardware malfunctions. This affects the localization of the entire network. To overcome this problem, we have reported a fault tolerant localization algorithm called clustering based DV-Hop. This algorithm filters out faulty nodes using K-means clustering and majority voting methods. The performance of the algorithm is then compared with other localization algorithms. The reported algorithm shows better localization accuracies and more stable performance under faulty conditions.

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Position and attitude estimation of a mobile robot in Lie group

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Journal of Institute of control, Robotics and systems 2020年第12期26卷 1099-1108页

作者： Jeong, Da Bin Ko, Nak Yong Song, Gyeongsub You, Sung Hyun Department of IT-Bio Convergence System Electronics Engineering Graduate School Chosun University Korea Republic of Department of IT-Bio Convergence System Electronics Engineering Chosun University Korea Republic of Department of IT-Bio Convergence System Control and Instrumentation Engineering Graduate School Chosun University Korea Republic of Department of Electronics Engineering Chosun University Korea Republic of

In this paper, the Lie group theory is used to estimate the position and attitude of a mobile robot. In the proposed method, a Kalman filter (KF) is implemented in a Lie group, specifically in a two-dimensional special Euclidean group SE(2). Position and attitude are represented as variables in SE(2). State transition is modeled using the exponential of the Lie algebra se(2), which corresponds to SE(2). Covariance of the estimates and correction of the predicted state are calculated using Lie algebra se(2). The performance of the proposed method is tested by conducting a simulation and is compared with the conventional extended KF, where Cartesian space coordinates and heading angle are used as state variables. The test results verify that the proposed method provides estimates that have smaller errors than those provided by the conventional extended KF. The Kalman gain and measurement innovation of the proposed method have superior convergence performance than the usual extended KF. © ICROS 2020.

关键词： Kalman filters

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Prediction of production performance for tapioca industry using LSTM neural network 16

Prediction of production performance for tapioca industry us...

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16th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2019

作者： Sonthited, Pacharaphol Koolpiruk, Diew Songkasiri, Warinthorn King Mongkut's University of Technology Thonburi Control System and Instrumentation Engineering Bangkok Thailand National Center for Genetic Engineering and Biotechnology Excellent Center of Waste Utilization and Management Bangkok Thailand

ISBN: (纸本)9781728133614

Cyber-physical system (CPS) is integrated between the virtual and physical worlds that uses service-oriented architecture (SOA) to manage service objects such as production, quality control, and maintenance engineering. Moreover, the CPS will be more effective by using the predictive ability to integrate some service object of CPS. This paper presents an intelligence function on the top CPS platform which will be the prediction of production performance to detect yield malfunction by using affect parameter with a starch yield of each production units such as production rate, starch content, loss in the process, a temperature of the flash dryer, and moisture content of starch for adjust the production process before an actual failure situation. The prediction model uses historian data from the factory with data from a mass balance model simulation and uses a Long-Short Term Memory (LSTM) processing to get the yield predicted results to indicate the trend of change in yield or irregularities that may occur, which will be the information for the design or modification of the production plan or control the production to be appropriate before abnormalities in real situations. This model has an average accuracy of 90.55% of test dataset which is predicted 1 day in advance. © 2019 IEEE.

关键词： Cyber Physical system

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ON DESIGNING FINITE TIME ITERATIVE LEARNING control BASED ON STEADY STATE FREQUENCY RESPONSE

arXiv

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arXiv 2021年

作者： Liu, Shuo Longman, Richard W. Panomruttanarug, Benjamas Department of Mechanical Engineering Boston University 110 Cummington Mall BostonMA02215 United States Mechanical Engineering Department of Mechanical Engineering Columbia University MC4703 500 West 120th Street New YorkNY10027 United States Department of Control System and Instrumentation Engineering King Mongkut’s University of Technology Thonburi Bangmod Tungkru Bangkok10140 Thailand

Iterative Learning control (ILC) is useful in spacecraft application for repeated high precision scanning maneuvers. Repetitive control (RC) produces effective active vibration isolation based on steady state frequency response. This paper considers the finite time ILC problem addressed using steady state frequency response, comparing two methods recently developed. One adapts for ILC the FIR filter design in RC that mimics the system’s steady state frequency response inverse, creating a filter designed for all frequencies from zero to Nyquist. Adjustment of gains near the beginning of the matrix need to be made because FIR gains are truncated there. The other approach uses a circulant matrix obtained from the Toeplitz matrix of Markov parameters. It is shown to give steady state frequency response for the discrete frequencies that can be seen in the number of time steps in the ILC tracking problem. The main aim of the paper is to compare the performance of each approach, and compare the ease of use. The inverse of the frequency response is used in RC to avoid the usually unstable inverse of the discrete time transfer function. Here the use in ILC has the same property. The performance and the robustness to model parameter error do not seem to have any significant difference. The main distinction is that the adjustment by steepest descent of a small number of gains in the Learning Gain Matrix is easier done in the FIR approach. Copyright © 2021, The Authors. All rights reserved.

关键词： Matrix algebra

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