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Contact analysis between rough surfaces considering the size-affected deformation behaviour of multi-scale asperities

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Tribology International 2022年 172卷 1页

作者： Zhang, Wenbo Lu, Zhendan Chen, Yunxia Zhang, Yawen School of Reliability and Systems Engineering Beihang University No. 37 Xueyuan Road Haidian District Beijing 100191 China Science and Technology on Reliability and Environmental Engineering Laboratory Beihang University Beijing 100191 China

Contact parameters such as the real contact area of rough surfaces depend on the interaction between asperities and the characteristic scale in which they remain. The high-stress deformation mechanism of the local contact spots exhibits size-dependent behaviour when the size of the asperities reaches a certain scale because of the scale effect. This causes deviations in the contact analysis, which can affect several tribological properties of the structural interface such as interface stiffness, fretting wear, and contact resistance. In this study, the deformation process affected by the scale effect is analysed using a finite element method that employs a conventional mechanism-based strain gradient plasticity (CMSGP) constitutive theory, whereas a full-scale elastoplastic contact model is developed for asperities at different size levels. Next, the contact analysis of rough surfaces is performed using the multi-scale contact theory proposed by Jackson and Streator (JS) considering this individual asperity model. The proposed model is validated using comparison with the refined finite element simulation analysis of rough surface contact that employs the CMSGP theory;further, the effect of morphology features on contact behaviour is discussed. The research results are conducive to the tribological design of small-size engineering interfaces. © 2022

关键词： Contact Multiscale asperities Rough surfaces Scale effect Strain gradient theory

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Modeling Grain Yield in China with Uncertain Time Series Analysis

Journal of Uncertain Systems

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Journal of Uncertain Systems 2022年第4期15卷

作者： Ye, Tingqing Kang, Rui School of Reliability and Systems Engineering Beihang University Beijing 100191 China Science and Technology on Reliability and Environmental Engineering Laboratory Beijing 100083 China Yunnan Innovation Institute Beihang University Kunming 650233 China

Grain yield is an important factor related to the stable operation of a country's social economy. This paper employs uncertain time series analysis (UTSA) to model rice grain yield in China, including order selection, parameter estimation, residual analysis, uncertain hypothesis test and forecast. By analyzing the characteristics of the residual plot, the reason of using uncertain time series analysis instead of probabilistic time series analysis is explained. © 2022 World Scientific Publishing Company.

关键词： grain yield Uncertain time series analysis uncertainty theory

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Reinforcement Learning-Based Energy Management for Hybrid engineering Vehicles

SSRN

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SSRN 2024年

作者： Liu, Huiying Yao, Yongming Li, Tianyu Du, Miaomiao Wang, Xiao Li, Haofa Li, Ming Key Laboratory of CNC Equipment Reliability Ministry of Education School of Mechanical and Aerospace Engineering Jilin University Changchun130022 China College of Electronic Information Engineering Changchun University Changchun130022 China Beijing Institute of Space Launch Technology Beijing100076 China Technology R&D Center of eDrive Special Vehicles China Aerospace Science and Technology Corporation Beijing100076 China

Fuel cell engineering vehicles utilize green energy with high energy conversion efficiency. Optimizing the utilization of hybrid energy storage systems is crucial for energy efficiency and self-sufficient operation. This study presents a unique energy management framework that utilizes reinforcement learning to regulate a fuel cell/ battery hybrid engineering vehicle. This novel framework helps the system achieve optimal energy management, even when confronted with demanding and ever-changing operational scenarios. The proposed strategy combines the ideas of Dyna algorithm and Deep Q-network (DQN) algorithm. Initially, a predictive model for determining working conditions is developed using the GRU neural network. The objective of this predictive model is to create a virtual depiction of the environment and accelerate the procedure of updating the model. The results from simulations and hardware-in-the-loop test demonstrate that the predictive model exhibits effective prediction capabilities, enabling the creation of accurate environment model even when limited sample data is available. The proposed strategy demonstrates superior performance compared to DQN and Q-Learning algorithms in terms of adaptability, real-time optimization, training efficiency, convergence speed, and energy conservation. When interacting with the environment, our proposed learning algorithm exhibits a significantly faster convergence rate. Furthermore, this strategy achieves a fuel economy of 95%, as determined by a dynamic programming-based method. Notably, this model-based deep reinforcement learning approach is practical and does not demand extensive training. An additional advantage of this energy management architecture is its utilization of a more accurate world model. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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The Effect of Rtp Pretreatment on Slip-Lines Of Argon Annealed Silicon Wafer

SSRN

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SSRN 2023年

作者： Chen, Guifeng Sun, Chenguang Wang, Hu Ai, Xingtian Zhang, Hui Xue, Zixuan Xie, Xinjian State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300132 China School of Materials Science and Engineering Hebei University of Technology Tianjin300132 China Hebei Engineering Laboratory of Photoelectronic Functional Crystals Hebei University of Technology Tianjin300130 China Zhonghuan Advanced Semiconductor Materials Co. Ltd Jiangsu Yixing214200 China

In this research, Rapid Thermal Process (RTP) pretreatment technology was used to study the slip-lines of 12-inch light boron-doped silicon wafer with Oxidation Induced Stacking Fault (OISF) ring which will be used for argon annealing. X-ray Diffraction Topography (XRT) test results were shown that Rapid Thermal Processing(RTP) pretreatment below 1250℃ would lead to the deterioration of slip-lines during argon annealing, and that RTP pretreatment no less than 1250℃ would eliminate slip-lines. Bulk Micro Defects(BMD) tests show that RTP pretreatment can deteriorate or eliminate slip-lines resulted from argon annealing. When the RTP pretreatment temperature is lower than 1250℃, the native BMD nuclei smaller than the critical size will eliminate. During argon annealing, the growth of the residual native BMD nuclei formed during ingot pulling process is the dominant process, while formation and growth of new nuclei are less, resulting in both the reduction of BMD density and broadening distribution of BMD size. Then we see the slip-lines of silicon wafer will become worse due to the increase of thermal stress in the silicon wafer. However, when the RTP pretreatment temperature is no less than 1250℃, the native BMD nuclei will be completely eliminated and a vacancy enriched layer will be formed in the silicon wafer. During argon annealing, vacancies promote the uniform nucleation of BMD, the density of BMD increases and the size distribution becomes narrow, and the thermal stress in the silicon wafer is relatively lower, thus the slip-lines are eliminated. © 2023, The Authors. All rights reserved.

关键词： Silicon wafers

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AMLP: Adaptive Masking Lesion Patches for Self-supervised Medical Image Segmentation

arXiv

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arXiv 2023年

作者： Wang, Xiangtao Wang, Ruizhi Zhou, Jie Lukasiewicz, Thomas Xu, Zhenghua State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Health Sciences and Biomedical Engineering Hebei University of Technology Tianjin China Institute of Logic and Computation Vienna University of Technology Vienna Austria Department of Computer Science University of Oxford Oxford United Kingdom

Self-supervised masked image modeling has shown promising results on natural images. However, directly applying such methods to medical images remains challenging. This difficulty stems from the complexity and distinct characteristics of lesions compared to natural images, which impedes effective representation learning. Additionally, conventional high fixed masking ratios restrict reconstructing fine lesion details, limiting the scope of learnable information. To tackle these limitations, we propose a novel self-supervised medical image segmentation framework, Adaptive Masking Lesion Patches (AMLP). Specifically, we design a Masked Patch Selection (MPS) strategy to identify and focus learning on patches containing lesions. Lesion regions are scarce yet critical, making their precise reconstruction vital. To reduce misclassification of lesion and background patches caused by unsupervised clustering in MPS, we introduce an Attention Reconstruction Loss (ARL) to focus on hard-to-reconstruct patches likely depicting lesions. We further propose a Category Consistency Loss (CCL) to refine patch categorization based on reconstruction difficulty, strengthening distinction between lesions and background. Moreover, we develop an Adaptive Masking Ratio (AMR) strategy that gradually increases the masking ratio to expand reconstructible information and improve learning. Extensive experiments on two medical segmentation datasets demonstrate AMLP's superior performance compared to existing self-supervised approaches. The proposed strategies effectively address limitations in applying masked modeling to medical images, tailored to capturing fine lesion details vital for segmentation tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Image segmentation

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A Comparison of Three Types of Computer-Based Procedures: An Experiment Using the Rancor Microworld Simulator 67th

A Comparison of Three Types of Computer-Based Procedures: An...

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67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023

作者： Hall, Anna Boring, Ronald L. Ulrich, Thomas A. Lew, Roger Velazquez, Michelle Xing, Jinding Whiting, Tim Makrakis, Georgios Michail Human Factors and Reliability Department Idaho National Laboratory Idaho FallsID United States Virtual Technology and Design Program University of Idaho MoscowID United States Psychology Department Idaho State University Pocatello Idaho United States Civil and Environmental Engineering Carnegie Mellon University PittsburghPA United States Computer Science Department Brigham Young University ProvoUT United States Computer Science Department University of Idaho Idaho FallsID United States

The nuclear power industry has historically used paper-based procedures, but a shift towards computer-based procedures (CBPs) has the potential to reduce human errors, alleviate mental workload, and improve work performance. Twentyseven participants were randomly assigned to one of three CBP types using the Rancor Microworld Simulator, and each performed two different types of operational scenarios (startup and loss of feedwater). The three CBP types varied in levels of digitalization. It was hypothesized that there would be less favorable impressions of the most basic procedures, and that these would demonstrate lower usability than types with greater digitalization. Overall, our predictions were partially supported with some interesting caveats, specifically with some performance benefits for CBPs that provided indicators but not embedded controls. We discuss our findings in terms of optimal levels of digitalization/automation within nuclear operations and suggest pathways for future directions. © 2023 Human Factors and Ergonomics Society.

关键词： Human-system integration Interface evaluation System design and analysis Usability

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A Tooth-Wise Dimensionality Reduction Approach Based on Encoder Signal for the Diagnosis of Gearbox 32nd

A Tooth-Wise Dimensionality Reduction Approach Based on Enco...

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32nd International Congress and Exhibition on Condition Monitoring and Diagnostic engineering Management, COMADEM 2019

作者： Liang, Kaixuan Zhao, Ming Ding, Chuancang Jiao, Jinyang Lin, Jing School of Mechanical Engineering Xi’an Jiaotong University Xi’an710049 China Science and Technology on Reliability and Environmental Engineering Laboratory School of Reliability and Systems Engineering Beihang University Beijing100083 China

ISBN: (纸本)9783030577445

As the planetary gearboxes are widely used in the industrial applications, a novel method is presented to detect the anomaly of planetary gearbox. In this work, the data from a rotary encoder are analyzed to get the fault information. The proposed approach mainly divided into three steps. Considering that the adopted values are angular displacements, the tooth-wise samples are obtained from the measured signal firstly. Then all the samples are mapped into a high-dimension space by kernel PCA (PCA) to find the most discriminative dimensions. Finally, the similarity measurement is taken among the tooth-wise samples to reveal the anomaly. The validity of proposed method is demonstrated both simulated signal and experimental data. © 2020, Springer Nature Switzerland AG.

关键词： Signal encoding

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Integration method of multi-source accelerated degradation testing data considering epistemic uncertainties and stress dependency 29

Integration method of multi-source accelerated degradation t...

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29th European Safety and reliability Conference, ESREL 2019

作者： Chen, Wen-Bin Li, Xiao-Yang Kang, Rui Hu, Yu-Qing Science and Technology on Reliability and Environmental Engineering Laboratory School of Reliability and Systems Engineering Beihang University Beijing100191 China Aerospace Science and Industry Corp Defense Technology R&T Center Beijing100854 China

ISBN: (纸本)9789811127243

Accelerated degradation testing (ADT) is commonly used to evaluate product reliability. Due to the fact that the test resources in conducting ADTs are usually limited, the collected degradation data are scarce, which brings epistemic uncertainties in reliability evaluation. Herein, the multi-source ADT data are usually integrated to decrease such uncertainties and achieve high accurate reliability assessments. However, the stress type sets of multiple ADTs are usually dependent, which makes it more difficult for the integration and is seldom taken into consideration in the state of art methods. In this paper, a novel integration method of multi-source ADT data are proposed to address such issues based on uncertainty theory and mutually exclusive set (MES) theory. First, the weight assignments for ADT datasets are given based on the union of the MESs of the accelerated stress types. Then, the uncertainty theory is introduced to model the degradation process of product, and the integration model of multi-source ADT datasets with assigned weights is proposed. A simulation study of the integration of two ADT datasets with different accelerated stress type sets is applied to verify the effectiveness of the proposed method. © 2019 European Safety and reliability Association. Published by Research Publishing, Singapore.

关键词： Integration testing

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Multi-objective Optimization of Repulsive Force Actuator for Vacuum Circuit Breaker

Multi-objective Optimization of Repulsive Force Actuator for...

引用

International Symposium on Discharges and Electrical Insulation in Vacuum

作者： Peiyuan Li Xiaoming Liu Hai Chen Wentao Jiang Yongjie Zhou State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin China School of Control Science and Engineering Tiangong University Tianjin China Shanghai Qiteng Electric Co. Ltd. Shanghai China

The fast DC vacuum switch driven by repulsive force actuator is the key equipment for the control and protection of the new energy power system. Its operating speed directly determines the interruption time of the DC vacuum switch. This paper takes fast 400V DC vacuum switch as the research object, studies the dynamic output characteristics, establishes the finite element numerical analysis model of electromagnetic repulsive force actuator, simulates and analyzes the influence of opening capacitors and charging voltage on the dynamic performance of fast switching. Moreover, the multi-objective artificial jellyfish optimizer is applied to design the repulsive force actuator. Based on the optimized 400V DC vacuum switch, the dynamic output performance of the fast switch has been obtained and analyzed. And the numerical simulation results show that the dynamic motion characteristics and energy conversion efficiency of the fast switch can be improved within 2.0ms.

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Prognostics of the ultrasonic motor based on an deep learning network model considering working signals and environmental factors 12

Prognostics of the ultrasonic motor based on an deep learnin...

引用

12th IEEE Global reliability and Prognostics and Health Management, PHM-Nanjing 2021

作者： Qin, Taichun Huang, Shouqing Liu, Ziwei Beijing Key Laboratory Of Environment And Reliability Test Technology For Aerospace Mechanical And Electrical Products Beijing Institute Of Spacecraft Environment Engineering Beijing China National Space Science Center Chinese Academy Of Sciences Beijing China

ISBN: (纸本)9781665401302

With the advantage of light weight, small volume, less electromagnetic radiation, fast dynamic response, and high energy density, ultrasonic motors have important applications in aerospace, automation and medical equipment. To realize the prognostics of an ultrasonic motor, this paper proposed a deep learning network model combining the convolutional neural network and the recurrent neural network. The convolutional neural network mines the correlation between different working parameters, while the recurrent neural network mines the temporal correlations of a single channel. Moreover, a fault injection test is carried out to obtain the baseline data and further validate the proposed prognostic model. The results show that this model can give accurate prognostic results under different environmental conditions. © 2021 IEEE.

关键词： Piezoelectric motors

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