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An adaptive fault detection strategy for Cz crystal growth process

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Mu, Lingxia Feng, Nan Zhang, Zhenhua Zhang, Youmin Zhang, Jian Xian University of Technology Crystal Growth Equipment and Systems Integration National Engineering Research Center Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian710048 China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Concordia University Department of Mechanical Industrial and Aerospace Engineering MontrealQCH3G 1M8 Canada

The monitoring and fault detection for the Czochralski (Cz) crystal growth process is important to ensure the quality of the produced mono-crystalline silicon. The Cz process is a typical multi-modes industrial process, which makes the detection difficult in distinguish the change caused by the fault or mode switching. In this paper, an adaptive fault detection strategy for Cz crystal growth process is proposed. Firstly, quality-related variables are selected from numerous process variables, based on which the training dataset is constructed. Then, a fault detection model is built based on slowly-varying feature and statics indicator. A model switching strategy and updating algorithm are designed to handle the abnormal situation caused by the mode switching or fault occurrence. Three representative experiments are conducted to verify the performance of the proposed strategy, including numerical cases, a publicly available dataset, and Cz crystal growth process from our laboratory. © 1963-2012 IEEE.

关键词： Crystal growth from melt

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Discrete Continuous Nonlinear control system for Non-Affine Periodic Action Plant

Discrete Continuous Nonlinear Control System for Non-Affine ...

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2020 International Russian Automation Conference, RusAutoCon 2020

作者： Eremin, E.L. Nikiforova, L.V. Shelenok, E.A. Amur State University Information and Control Systems Department Blagoveshchensk Russia Pacific National University Automation and System Engineering Department Khabarovsk Russia

ISBN: (纸本)9781728161303

In the present paper authors discusses the problem of construct the discrete algorithms of nonlinear-periodic control system for one class of non-affine continuous plants which working in the priory uncertainty conditions. As methods to solve the posed in paper problem hyperstability criterion, Ldissipativity conditions and continuous models method are used. With the help of numerical experiments it is depicted the operating quality of the proposed hybrid nonlinear-periodic control system. The obtained results may be useful for construction the automated control system for dynamic plants which mathematical model contains non-linearity with respect to input signal. The paper results may be useful for construct the control systems for the class of non-affine dynamic plants with mathematical models are equivalent discussed plant's model. © 2020 IEEE.

关键词： Quality control

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Recurrent Attentional Reinforcement Learning for Machinery Fault Diagnosis

SSRN

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SSRN 2024年

作者： Tang, Zhenhui Wang, Jingcheng Wu, Shunyu The Department of Automation The Key Laboratory of System Control and Information Processing Ministry of Education of China The Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University No.800 Dongchuan Road Shanghai200240 China The SJTU Sanya Yazhou Bay Institute of Deepsea Science and Technology Sanya572024 China The Autonomous Systems and Intelligent Control International Joint Research Center Xi’an Technological University Xi’an710021 China

Recognizing fault types of machinery system is a fundamental but challenging task in industrial application. Although remarkable progress has been attained by learning fault features and predicting the corresponded fault type with deep neural networks, the existing fault diagnosis pipelines usually learn non-discriminative information. Contextual sequence dependency between the localized time fragments is often ignored. To deal with these problem, a recurrent attention framework with reinforcement learning is proposed to find a series of informative features of local time fragments related to different faults in an iterative manner. Fault labels are further predicted on these time fragments. The proposed framework also explicitly models long-term dependencies among these attentional time fragments to capture historical fault information. Experiments on two typical machinery systems, bearing system and hydraulic system, show that the proposed framework achieves superior diagnosis performance and increases no computation burden on CPU. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Challenges and Solutions for Practical Implementation of Process Bus Based Substation Protection and Automation system

Challenges and Solutions for Practical Implementation of Pro...

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Environment and Electrical engineering (EEE-AM), Asia Meeting on

作者： Kevin Soetomo Koichi Hamamatsu Dinh Huu Thuan Nguyen Manh Linh Lai Vu Quang Makoto Okai Engineering Dept. Power Grid System Solutions Toshiba Energy Systems & Solutions Corporation Kawasaki Japan Technical Department Southern Power Corporation (EVNSPC) Ho Chi Minh City Vietnam Engineering Dept. Toshiba Transmission & Distribution Systems (Vietnam) Ltd. Hanoi Vietnam Sales & Engineering Division Toshiba Transmission & Distribution Systems (Vietnam) Ltd. Hanoi Vietnam Protection and Control Dept. Toshiba Energy Systems & Solutions Corporation Fuchu Japan

The protection and control system in substations has undergone significant evolution since the era of hardwired systems. In recent years, the increasing trend of digital transformation (DX) across various fields, including protection and automation systems, has led to the promotion of IEC 61850 process bus-based digital substations. However, recent analysis and evaluation have revealed numerous challenges in various aspects, such as technical issues, system performance, test methods, maintenance, and economic considerations. Moreover, many of these challenges lie outside the scope of international standards like IEC 61850 and IEC 61869. As a result, the worldwide implementation of digital substations has been hindered. This paper aims to describe the issues encountered during the implementation of process bus technology and propose solutions that focus on optimizing system configuration based on our experience in implementing digital substation projects and developing MU and IED. Addressing these issues is crucial to fully unlocking the potential of digital substations. One of the most promising advantages is the availability of digital data collected from substation equipment. By utilizing this data, overall power system operational efficiency can be enhanced, and equipment management can be optimized. Predictive maintenance can be implemented, enabling the early detection of potential equipment failures, minimizing unplanned outages, and reducing the need for emergency repairs, which contribute to unnecessary carbon emissions and equipment downtime. Ultimately, digital substations empower end-users to reduce greenhouse gas emissions, improve energy efficiency, and seamlessly integrate power systems, thereby supporting the carbon-neutral initiative and facilitating the transition towards a sustainable energy future.

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Self-triggered Resilient Stabilization of Linear systems with Quantized Output

arXiv

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arXiv 2023年

作者： Liu, Wenjie Wakaiki, Masashi Sun, Jian Wang, Gang Chen, Jie Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chonqing401120 China Graduate School of System Informatics Kobe University Hyogo657-8501 Japan Department of Control Science and Engineering Tongji University Shanghai201804 China

This paper studies the problem of stabilizing a self-triggered control system with quantized output. Employing a standard observer-based state feedback control law, a self-triggering mechanism that dictates the next sampling time based on quantized output is co-developed with an output encoding scheme. If, in addition, the transmission protocols at the controller-to-actuator (C-A) and sensor-to-controller (S-C) channels can be adapted, the self-triggered control architecture can be considerably simplified, leveraging a delicate observer-based deadbeat controller to eliminate the need for running the controller in parallel at the encoder side. To account for denial-of-service (DoS) in the S-C channel, the proposed output encoding and self-triggered control schemes are further made resilient. It is shown that a linear time-invariant system can be exponentially stabilized if some conditions on the average DoS duration time are met. There is a trade-off between the maximum inter-sampling time and the resilience against DoS attacks. Finally, a numerical example is presented to demonstrate the practical merits of the proposed self-triggered control schemes and associated theory. © 2023, CC BY.

关键词： controllers

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COMPUTATIONAL FLUID-STRUCTURE INTERACTION FRAMEWORK FOR SIMULATING CHARACTERISTIC DEFORMATIONS IN INSECT FLAPPING WINGS 9

COMPUTATIONAL FLUID-STRUCTURE INTERACTION FRAMEWORK FOR SIMU...

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9th International Conference on Computational Methods for Coupled Problems in Science and engineering, COUPLED PROBLEMS 2021

作者： Onishi, Minato Ishihara, Daisuke Department of Computer Science and System Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka Fukuoka820-8502 Japan Department of Intelligent and Control Systems Kyushu Institute of Technology Kyushu Institute of Technology 680-4 Kawazu Iizuka Fukuoka820-8502 Japan

In this study, a computational fluid-structure interaction (FSI) framework for characteristic deformations in insect's wings is proposed. The proposed framework consists of a pixel wing model using a structured shell finite element mesh, a projection method for the monolithic FSI monolithic equations using an algebraic splitting, and the FSI dynamic similarity law to measure dynamic similarity between model's and actual insect's flights. It is shown that the proposed framework can directly simulate passive feathering and cambering in insect's wings caused by the FSI, whose magnitudes are very close to those of actual insects. © 2021 9th International Conference on Computational Methods for Coupled Problems in Science and engineering, COUPLED PROBLEMS 2021. All rights reserved.

关键词： Fluid structure interaction

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Recurrent Attentional Reinforcement Learning for Fault Diagnosis of Hydraulic system

Recurrent Attentional Reinforcement Learning for Fault Diagn...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Zhenhui Tang Ru Liu Kang Lou Chaojian Gao Jingcheng Wang SJTU Sanya Yazhou Bay Institute of Deepsea Science and Technology Sanya China Department of Automation Shanghai Jiao Tong University Shanghai China Shanghai Marine Equipment Research Institute Shanghai China Department of Automation the Key Laboratory of System Control and Information Processing Ministry of Education of China and the Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University Xi'an China

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Recognizing fault types of machinery system is a fundamental but challenging task in industrial application. Although data-driven fault diagnosis method attains remarkable progress by learning fault features automatically, the existing data-driven fault diagnosis pipelines learn non-discriminative feature. To deal with these problems, a new data-driven fault diagnosis method with recurrent attentional module is proposed to find a sequence of informative features by localizing distinguishing time fragments about each individual faults iteratively. The contextual sequence dependency between the localized time fragments is enhanced. Then, the fault types are further predicted on localized time fragments. The proposed framework also explicitly models long-term dependencies among these attentional time fragments to capture historical fault information. Experiments on hydraulic system show that the proposed framework achieves superior diagnosis performance and computation efficiency.

关键词： Fault diagnosis Location awareness Accuracy Computational modeling Pipelines Reinforcement learning Hydraulic systems Computational efficiency Information technology

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Modeling, simulation and experiment of an origami robot with a coupled bar-hinge mechanism

Modeling, simulation and experiment of an origami robot with...

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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Junpeng Mai Hanzhao Shao Shaojie Liu Yuanzhuo Zhang Liangming Chen Huijuan Feng School of System Design and Intelligent Manufacturing and Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology Shenzhen P. R. China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen P. R. China Department of Mechnical and Energy Engineering Southern University of Science and Technology Shenzhen P. R. China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This paper aims to analyze the motion behavior of an origami robot with a coupled bar-hinge mechanism. By disassembling the planar six-hinge mechanism into two planar four-hinge mechanisms with coupled motion, this paper derives the kinematics of the planar six-hinge mechanism based on the algebraic differential kinematics of the planar four-hinge motions. The rotational angle change and the moving step length of the origami robot are further calculated. Finally, the theoretical motion model is verified with the motion simulation data of the planar six-hinge mechanism origami robot in SolidWorks and the experimental data of the physical model. This verification proves the feasibility of the theoretical analysis, simulation model, and physical model.

关键词： Solid modeling Analytical models Prototypes Kinematics Three-dimensional printing Mathematical models Data models

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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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Platoon-Based Distributed control for Automated Material Handling systems

Platoon-Based Distributed Control for Automated Material Han...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Alessandro Bozzi Jose-Fernando Jimenez Camilo Hernandez-Rodriguez Eliana-Maria Gonzalez-Neira Damien Trentesaux Department of Informatics Bioengineering Robotics and Systems Engineering (DIBRIS) University of Genova Italy Laboratory System and Materials for Mechatronics (SYMME) Université Savoie Mont Blanc Annecy France Industrial Engineering Department Pontificia Universidad Javeriana Bogota Columbia Laboratory of Industrial and Human Automation Control Mechanical Engineering and Computer Science (LAMIH) Université Polytechnique Hauts-de-France Valenciennes France

Smart manufacturing systems combine collaborative and autonomous control systems to provide optimal performance and respond to volatile demands. A key component of smart manufacturing is material management, as raw materials, work-in-progress, and finished products must be transported to the right location at the right time. However, during the production phase, it is imperative to establish an optimal traffic control scheme in order to avoid congestion and optimize material flow. This paper proposes a platooning-based control procedure implemented in a virtual agent-based manufacturing environment to increase the material flow efficiency on a manufacturing shop floor. An analysis of the production makespan and an indicator of the level of congestion in the material handling system was conducted in order to determine productivity improvements. An agent-based simulation is used to test the effectiveness of the novel platooning approach versus a traditional basic approach. A multivariate analysis of variance (MANOVA) reveals that the inclusion of a platoon-based procedure improves production performance and reduces congestion risks.

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