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SSRN 2025年

作者： Qi, Shucheng Zhu, Jiyuan Key Laboratory of Advanced Manufacturing and Automation Technology Guilin University of Technology Guilin541006 China

In this study, a phytate conversion coating was first obtained on AZ91D Mg alloys, and then a CeO2 coating with superhydrophobic properties was prepared using a one-step hydrothermal method with stearic acid. The outer layer displayed a spherical aggregation state, which formed a dense covering over the inner phytic acid conversion layer. The prepared coating samples exhibited excellent superhydrophobic and self-cleaning properties. Furthermore, the composite coatings exhibited satisfactory adhesion to the substrate. Concurrently, the corrosion current density of the coated samples was reduced by four orders of magnitude compared with that of the uncoated samples, which illustrates significant corrosion durability. When the coating samples are damaged by external forces, cerium ions may be gradually released from the surrounding damage area and transformed into new cerium-based compounds, preventing further expansion of corrosion, which exhibit self-repairing properties. © 2025, The Authors. All rights reserved.

关键词： Magnesium alloys

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Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance with EDA and Multi-Channel CNN

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IEEE Access 2025年 13卷 31978-31991页

作者： Wahyu Trisna, Komang Huang, Jinjie Chen, Yuanjian Gede Juliana Eka Putra, I. Harbin University of Science and Technology School of Computer Science and Technology Harbin150080 China Primakara University Department of Informatic Engineering Denpasar Bali80226 Indonesia Harbin University of Science and Technology Key Laboratory of Advanced Manufacturing and Intelligence Technology Harbin150080 China

The rapid growth of social media has revolutionized the way individuals share and access opinions, generating vast amounts of textual data containing diverse sentiments. Sentiment analysis enables organizations to derive valuable insights from this data, facilitating improved decision-making. However, the limited availability of labeled datasets and challenges related to data imbalance often hinder the development of robust sentiment analysis models. In this study, we propose a novel framework dynamic Easy Data Augmentation (EDA) technique with a Multi-Channel Convolutional Neural Network (MCNN) to address these issues. The EDA techniques including synonym replacement (SR), random insertion (RI), random deletion (RD), and random swap (RS), enrich the training data by introducing diversity, thereby enhancing model robustness. The MCNN architecture effectively captures local patterns in text using multiple filter sizes, enabling comprehensive feature extraction with low computational overhead. Furthermore, the integration of Word2Vec embeddings ensures meaningful text representation, leveraging context-independent word relationships for improved sentiment analysis. Experimental evaluations demonstrate the effectiveness of the proposed approach, highlighting significant improvements in F1-score compared to baseline models. The findings underscore the potential of dynamic text augmentation and efficient deep learning architectures to overcome the challenges of limited training data, offering a scalable solution for sentiment analysis in real-world applications. Additionally, the proposed model achieves an average performance improvement of 11.34% over previous models. © 2025 The Authors.

关键词： Convolutional neural networks

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A Bolt Fastening Robot System Based on Hybrid Vision and Its Effect Analysis of Process Parameters on Fastening Performance 17th

A Bolt Fastening Robot System Based on Hybrid Vision and Its...

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17th International Conference on Intelligent Robotics and Applications, ICIRA 2024

作者： Chen, Jianzhou Liu, Zhifeng Xu, Jingjing Hun, Lianming Tao, Long Peng, Kaiguo Key Laboratory of Advanced Manufacturing and Intelligent Technology for High-End CNC Equipment Jilin University Changchun130025 China Key Laboratory of CNC Equipment Reliability Ministry of Education Jilin University Changchun130025 China Institute of Advanced Manufacturing Technology and Institute of Advanced Manufacturing and Intelligent Technology Beijing University of Technology Beijing100124 China Jiangxi Tianyue Automobile Parts Co. Ltd. Jiangxi336000 China

ISBN: (纸本)9789819607761

With the improvement of industrial automation levels, the demand for automatic assembly increases. In this work, a bolt fastening robotic system based on hybrid vision is proposed to enhance environmental adaptability and reduce costs. In its fastening strategy, the hole pose is determined accurately using hybrid vision, which uses the scene camera to obtain the rough pose and uses the end-effector camera to obtain the precision pose based on its high-quality images acquisition. After the positioning, the efficiency of the fastening process is significantly influenced by motion parameters of the robotic system, such as the angle between bolt and hole, the speed of the end-effector, and the rotation speed of the tool. The maximum allowable angle of bolt and hole is calculated. The M10 bolt can be smoothly inserted into the hole when angle is less than 2.92 degrees. The experiments were conducted to investigate how changes in these motion parameters collectively impact bolt fastening efficiency. Changes in the angle between the bolt and the hole do not affect the robotic bolt fastening efficiency. These results provide the significant theoretical basis for the selection of process parameters of the robotic system, considering the specific requirements of the bolt assembly task. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Bolts

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Effect of orbital symmetry on atomic ionization in near-infrared laser fields

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Chinese Physics B 2025年第1期34卷 289-292页

作者： Manqi Xu Shilin Hu Li Guo Jing Chen Research Center for Advanced Optics and Photoelectronics Department of PhysicsCollege of ScienceShantou UniversityShantou 515063China Key Laboratory of Intelligent Manufacturing Technology of MOE Shantou UniversityShantou 515063China Department of Physics Shanghai Normal UniversityShanghai 200234China Hefei National Research Center for Physical Sciences at the Microscale and School of Physical Sciences Department of Modern PhysicsUniversity of Science and Technology of ChinaHefei 230026China Shenzhen Key Laboratory of Ultraintense Laser and Advanced Material Technology Center for Advanced Material Diagnostic Technologyand College of Engineering PhysicsShenzhen Technology UniversityShenzhen 518118China

We have performed a comparative study of the photoelectron spectra adopting different initial states(2s or 2_(p0))of hydrogen atoms in a near-infrared laser pulse by using the full three-dimensional time-dependent Schr?dinger *** is demonstrated that the atomic photoelectron spectra oscillate out of step as a function of electron kinetic energies for different initial states(2s or 2_(p0)),which is well reproduced by the simulations based on strong field approximation,and the above distinct feature is ascribed to the different interferences from the partial electron wave packets detached by positive and negative electric fields for different initial states of 2s and 2_(p0).

关键词： orbital symmetry photoelectron spectra strong-field approximation

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Defects response to precoated adhesive in Al/steel friction stir welded joint

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Journal of manufacturing Processes 2025年 141卷 1109-1118页

作者： Huang, Weiben Ding, Zhijie Li, Peng Zhao, Peng Zhou, Dianwu Huang, Yongxian Meng, Xiangchen Li, Yongbing Ma, Yunwu Dong, Honggang School of Materials Science and Engineering Dalian University of Technology Dalian116024 China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha410082 China State Key Laboratory of Precision Welding & Joining of Materials and Structures Harbin Institute of Technology Harbin150001 China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China

Friction stir welding (FSW) has been applied for welding dissimilar materials in advanced manufacturing industries such as shipbuilding, automotive and aerospace. For the broad popularization of adhesive in FSW, the innovative coupling method of friction stir welding-adhesive bonding (FSW-AB) technology was designed to join 5A06 aluminum alloy to 304 stainless steel. The joints were fabricated using a single-component structural adhesive applied manually in the pre-lap zone. The joints were then cured by the heat generated from FSW. Macrostructure, defect generation and tensile shear performances of the joints obtained using three different rotation speeds and different adhesive thickness were studied. The adhesive prevented direct plate contact, but the FSW-AB joint showed more flash. Adhesive expansion occurred on the advancing side due to structural asymmetry and uneven heat dissipation. Compared to conventional FSW, the joints produced by FSW-AB exhibited significantly reduced hook defects in the pin-affected zone, a smoother distribution of hardness across the weld cross-section, and notably elevated hardness on the retreating side of the base metal outside the shoulder. It is attributed to the difference in the degree of crystallization between the two caused by the difference in heat dissipation rate. The ultimate tensile shear load of the FSW-AB joint reached 93.3 % of the conventional FSW joint at 1200 rpm stirring speed and 0.25 mm adhesive thickness. Furthermore, the fracture modes of FSW-AB joints were mainly normal fracture and shear fracture. © 2025 The Society of manufacturing Engineers

关键词： Vickers hardness

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Research on wear state prediction of ball end milling cutter based on entropy measurement of tool mark texture images

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Journal of Central South University 2025年第1期32卷 174-188页

作者： LI Mao-yue LU Xin-yuan LIU Ze-long ZHANG Ming-lei Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of EducationHarbin University of Science and TechnologyHarbin 150080China

Efficient tool condition monitoring techniques help to realize intelligent management of tool life and reduce tool usage *** this paper,the influence of different wear degrees of ball-end milling cutters on the texture shape of machining tool marks is investigated,and a method is proposed for predicting the wear state(including the position and degree of tool wear)of ball-end milling cutters based on entropy measurement of tool mark texture ***,data samples are prepared through wear experiments,and the change law of the tool mark texture shape with the tool wear state is ***,a two-dimensional sample entropy algorithm is developed to quantify the texture ***,the processing parameters and tool attitude are integrated into the prediction process to predict the wear value and wear position of the ball end milling *** testing,the correlation between the predicted value and the standard value of the proposed tool condition monitoring method reaches 95.32%,and the accuracy reaches 82.73%,indicating that the proposed method meets the requirement of tool condition monitoring.

关键词： ball-end cutter wear tool condition monitoring surface texture texture quantifier sample entropy

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Distribution network gray-start and emergency recovery strategy with pumped storage unit under a typhoon

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Global Energy Interconnection 2025年第1期8卷 121-133页

作者： Zhenguo Wang Hui Hou Chao Liu Shaohua Wang Zhengtian Li Xiangning Lin Te Li Research Institute of State Grid Zhejiang Electric Power Company Hangzhou 310014PR China School of Automation Wuhan University of TechnologyWuhan 430070PR China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and TechnologyWuhan 430074PR China

Typhoons can cause large-area blackouts or partial outages of distribution *** define a partial outage state in the distribution network as a gray state and propose a gray-start strategy and two-stage distribution network emergency recovery framework.A phase-space reconstruction and stacked integrated model for predicting wind and photovoltaic generation during typhoon disasters is proposed in the first *** provides guidance for second-stage post-disaster emergency recovery *** emergency recovery scheduling model is established in the second stage,and this model is supported by a thermal power-generating unit,mobile emergency generators,and distributed *** generation includes wind power generation,photovoltaics,fuel cells,***,we con-sider the gray-start based on the pumped storage unit to be an important first step in the emergency recovery *** model is val-idated on the improved IEEE 33 node system,which utilizes data from the 2022 super typhoon“Muifa”in Zhoushan,Zhejiang,*** indicate the superiority of a gray start with a pumped storage unit and the proposed emergency recovery strategy.

关键词： Wind and photovoltaic generation prediction Pumped storage unit Gray-start Distribution network Emergency recovery strategy

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Efficient blocked symmetric compressed sparse column method for finite element analysis

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Frontiers of Mechanical Engineering 2025年第1期20卷 87-104页

作者： Yingjun WANG Shijie LUO Jinyu GU Yuanfang ZHANG National Engineering Research Center of Novel Equipment for Polymer Processing The Key Laboratory of Polymer Processing Engineering of the Ministry of EducationGuangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced ManufacturingSouth China University of TechnologyGuangzhou 510641China Shien-Ming Wu School of Intelligent Engineering South China University of TechnologyGuangzhou 511442China

In finite element analysis(FEA),optimizing the storage requirements of the global stiffness matrix and enhancing the computational efficiency of solving finite element equations are pivotal *** address these goals,we present a novel method for compressing the storage of the global stiffness matrix,aimed at minimizing memory consumption and enhancing FEA *** method leverages the block symmetry of the global stiffness matrix,hence named the blocked symmetric compressed sparse column(BSCSC)*** also detail the implementation scheme of the BSCSC method and the corresponding finite element equation solution *** approach optimizes only the global stiffness matrix index,thereby reducing memory requirements without compromising FEA computational *** then demonstrate the efficiency and memory savings of the BSCSC method in FEA using 2D and 3D cantilever beams as *** addition,we employ the BSCSC method to an engine connecting rod model to showcase its superiority in solving complex engineering ***,we extend the BSCSC method to isogeometric analysis and validate its scalability through two examples,achieving up to 66.13%memory reduction and up to 72.06%decrease in total computation time compared to the traditional compressed sparse column method.

关键词： finite element analysis global stiffness matrix blocked symmetric property memory reduction isogeometric analysis

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Non-Line-of-Sight Multipath Classification Method for BDS Using Convolutional Sparse Autoencoder with LSTM

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Tsinghua Science and technology 2025年第1期30卷 68-86页

作者： Yahang Qin Zhenni Li Shengli Xie Bo Li Ming Liu Victor Kuzin School of Automation Guangdong University of Technologyand also with Guangdong-Hong Kong-Macao Joint Laboratory for Smart Discrete ManufacturingGuangzhou 510006China School of Automation Guangdong University of TechnologyGuangdong Key Laboratory of IoT Information TechnologyGuangzhou 510006China 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Key Laboratory of Intelligent Information Processing and System Integration of IoTMinistry of EducationGuangzhou 510006China Department of Electronic and Computer Engineering Hong Kong University of Science and TechnologHong Kong 999077China Academician of Russian Engineering Academy Moscow Moscow 125009Russia

Multipath signal recognition is crucial to the ability to provide high-precision absolute-position services by the BeiDou Navigation Satellite System(BDS).However,most existing approaches to this issue involve supervised machine learning(ML)methods,and it is difficult to move to unsupervised multipath signal recognition because of the limitations in signal *** by an autoencoder with powerful unsupervised feature extraction,we propose a new deep learning(DL)model for BDS signal recognition that places a long short-term memory(LSTM)module in series with a convolutional sparse autoencoder to create a new autoencoder ***,we propose to capture the temporal correlations in long-duration BeiDou satellite time-series signals by using the LSTM module to mine the temporal change patterns in the time ***,we develop a convolutional sparse autoencoder method that learns a compressed representation of the input data,which then enables downscaled and unsupervised feature extraction from long-duration BeiDou satellite series ***,we add an l_(1/2) regularizer to the objective function of our DL model to remove redundant neurons from the neural network while ensuring recognition *** tested our proposed approach on a real urban canyon dataset,and the results demonstrated that our algorithm could achieve better classification performance than two ML-based methods(e.g.,11%better than a support vector machine)and two existing DL-based methods(e.g.,7.26%better than convolutional neural networks).

关键词： convolutional sparse autoencoder BeiDou Navigation Satellite System(BDS) long short-term memory(LSTM) multipath classification

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Optimization for furnace-assisted laser cladding process parameter of crack-free ceramic-based coating by response surface methodology

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Ceramics International 2025年第9期51卷 11735-11746页

作者： Yong, Zhao Wang, Yunfei Yang, Gaolin Shi, Yuelin Zhang, QunLi Yao, Jianhua College of Mechanical Engineering Zhejiang University of Technology Hangzhou310023 China Key Laboratory of Special Purpose Equipment and Advanced Processing Technology of Ministry of Education Zhejiang University of Technology Hangzhou310023 China Institute of Laser Advanced Manufacturing Zhejiang University of Technology Hangzhou310023 China Zhoushan Dingzun Intelligent Technology Co. LTD Zhoushan316031 China

Ceramic-based coating, recognized as advanced surface treatment material, which is widely utilized across various sectors including aerospace, automotive, and industrial manufacturing. This extensive application is attributed to their remarkable properties such as wear resistance, high-temperature tolerance, and corrosion resistance. However, ceramic phase of the coating experienced excessive residual stress due to rapid cooling and heating effects, during the laser cladding process. Thus, the formation of cracks and pores in the coating is a common issue, posing significant challenge to the preparation of ceramic-based coating. This study employed the response surface methodology to optimize the process parameters of furnace-assisted laser cladding for fabricating 60WC coating on 45# steel substrate. The effects of laser power, scanning rate, powder feeding rate, and preheating temperature on coating height, dilution rate and micro-hardness were investigated comprehensively in order to achieve a crack-free 60WC coating. The results indicate that the synergistic effect of laser scanning speed and preheating temperature is of the utmost significance for attaining crack-free coatings with high hardness. Through the adjustment of these two parameters, a coating featuring high hardness and no cracks can be acquired. And it was determined by RSM that the optimal coating quality was achieved under the following conditions: 2586.13 W laser power, 740.74 mm/min laser scanning speed, 400 °C preheating temperature, and 22.0 g/min powder feeding speed, with no discernible macroscopic or microscopic cracks present. © 2025

关键词： Preheating

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