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Theoretical Model Construction and Static Performance Analysis of Multi-Leaf Journal Foil Bearings

Journal of Tribology 2025年第7期147卷 074101页

作者： Hu, Yang Ding, Pengjing School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai200072 China

Multi-leaf journal foil bearing (MLJFB) structures are complex, making performance prediction challenging, and the accurate prediction of gas film thickness and pressure distributions is crucial. In this study, comsol finite-element software was used to establish an initial foil assembly and structural deformation simulation model for an MLJFB with bump foils. Using matlab, a compressible gas lubrication model was established and solved using the finite volume method. Real-time data transfer between comsol and matlab enabled a fully coupled fluid-structure interaction simulation. This model meticulously accounts for the pre-tension force in the multi-leaf bearing assembly, contact friction between adjacent foils, and the interaction between the top foil and gas film pressure. The effects of journal movement distance, direction, and top foil overlapping ratio on the bearing capacity as well as the effects of different external load directions on the journal equilibrium position were analyzed based on this model. The results indicate that increasing the top foil overlapping ratio enhances the bearing capacity of the MLJFB. Furthermore, compared to the direction of the top foil overlap position, external loads applied in the direction of the top foil midpoint are more beneficial for bearing operational stability. Copyright © 2024 by ASME.

关键词： MATLAB

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Strain sensor on a chip for quantifying the magnitudes of tensile stress on cells

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Microsystems & Nanoengineering 2024年第3期10卷 305-315页

作者： Yuyin Zhang Yue Wang Hongze Yin Jiahao Wang Na Liu Songyi Zhong Long Li Quan Zhang Tao Yue School of Mechatronics Engineering and Automation Shanghai UniversityShanghaiChina School of Future Technology Shanghai UniversityShanghaiChina Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhouChina Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai UniversityShanghaiChina Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghaiChina

During cardiac development,mechanotransduction from the in vivo microenvironment modulates cardiomyocyte growth in terms of the number,area,and arrangement ***,the response of cells to different degrees of mechanical stimuli is ***-on-a-chip,as a platform for investigating mechanical stress stimuli in cellular mimicry of the in vivo microenvironment,is limited by the lack of ability to accurately quantify externally induced ***,previous technology lacks the integration of external stimuli and feedback sensors in microfluidic platforms to obtain and apply precise amounts of external ***,we designed a cell stretching platform with an in-situ *** in-situ liquid metal sensors can accurately measure the mechanical stimulation caused by the deformation of the vacuum cavity exerted on *** platform was applied to human cardiomyocytes(AC16)under cyclic strain(5%,10%,15%,20 and 25%),and we found that cyclic strain promoted cell growth induced the arrangement of cells on the membrane to gradually unify,and stabilized the cells at 15%amplitude,which was even more effective after 3 days of *** platform’s precise control and measurement of mechanical forces can be used to establish more accurate in vitro microenvironmental models for disease modeling and therapeutic research.

关键词： stress deformation arrangement

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Study on the interactive deformation of bone needles and circum-pelvic soft tissue

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High Technology Letters 2024年第3期30卷 297-303页

作者： ZHANG Famin LEI Jingtao School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444P.R.China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai 200444 P.R.China

During the robot-assisted pelvic fracture reduction,the needle-tissue interactive deformation characteristic is not clear,which affects the accuracy of robotic *** this paper,a layered rig-id-flexible coupling model is proposed,and the needle-tissue interactive deformation under the load-ing is analyzed by the Rayleigh-Ritz method,in accordance with the principle of minimum potential *** pelvic musculoskeletal tissue is reversely reconstructed,and the structure of the bone is segmented into cancellous bone and cortical *** Mooney-Rivlin five-parameter hyperelastic model is used to simulate muscle,and the Ogden hyperelastic model is used to simulate adipose *** element simulation is performed by loading different magnitudes of *** accuracy of the rigid-flexible coupling model is 0.432 mm,which indicates the correctness of the needle-tis-sue interactive deformation theory analysis.

关键词： pelvic fracture reduction rigid-flexible coupling needle-tissue interactive de-formation

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A trajectory-level robot skill learning method based on fuzzy systems

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Science China(Information Sciences) 2025年第5期68卷 38-52页

作者： Chao ZENG Zhen DENG Boyang TI Yongsheng GAO Department of Computer Science University of Liverpool School of Mechanical Engineering and Automation Fuzhou University State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics and System Harbin Institute of Technology

Learning from demonstration(LfD) allows for the effective transfer of human manipulation skills to a robot by building a model that represents these skills based on a limited number of demonstrated ***,a skilllearning model that can comprehensively satisfy multiple requirements,such as computational complexity,modeling accuracy,trajectory smoothness,and robustness,is still ***,this work aims to provide such a model by employing fuzzy ***,we introduce an LfD model named Takagi-Sugeno-Kang fuzzy system-based movement primitives(TSKFMPs),which exploits the advantages of the fuzzy theory for effective robotic imitation learning of human *** work formulates the TSK fuzzy system and gradient descent(GD) as imitation learning models,leveraging recent advancements in GD-based optimization for fuzzy *** study takes a two-step strategy.(ⅰ) The input-output relationships of the model are established using TSK fuzzy systems based on demonstration *** this way,the skill is encoded by the model parameter in the latent space.(ⅱ) GD is used to optimize the model parameter to increase the modeling accuracy and trajectory *** further explain how learned trajectories are adapted to new task scenarios through local *** conduct multiple tests using an open dataset to validate our method,and the results demonstrate performance comparable with those of other ***,we implement it in a real-world case study.

关键词： robot skill learning movement primitives TSK fuzzy systems gradient descent robotics

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Fabricating AC/DC nanogenerators based on single ZnO nanowires by using a nanomanipulator in a scanning electron microscope

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Nanotechnology and Precision Engineering 2024年第2期7卷 25-31页

作者： Mei Liu Mengfan He Aristide Djoulde Lingdi Kong Weilin Su Xin Bai Jinbo Chen Jinjun Rao Zhiming Wang Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 200444China Guangdong Provincial Key Laboratory of Fuel Cell Technology School of Chemistry and Chemical EngineeringSouth China University of TechnologyGuangzhou 510641China

Single zinc oxide nanowires(ZnO NWs)are promising for nanogenerators because of their excellent semiconducting and piezoelectric properties,but characterizing the latter efficiently is *** reported here,an electrical breakdown strategy was used to construct single ZnO NWs with a specific *** the high operability of a nanomanipulator in a scanning electron microscope,ZnO-NW-based twoprobe and three-probe structures were constructed for fabricating AC/DC nanogenerators,*** a ZnO NW,an AC output of between−15.31 mV and 5.82 mV was achieved,while for a DC nanogenerator,an output of24.3 mV was ***,the three-probe structure’s output method was changed to verify the distribution of piezoelectric charges when a single ZnO NW is bent by a probe,and DC outputs of different amplitudes were *** study provides a low-cost,highly convenient,and operational method for studying the AC/DC output characteristics of single NWs,which is beneficial for the further development of nanogenerators.

关键词： Zinc oxide nanowire Piezoelectric properties Nanomanipulator SEM AC/DC nanogenerators

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Ensemble-based Offline Data-driven Evolutionary Optimization for Operation Parameter of Blast Furnace 20

Ensemble-based Offline Data-driven Evolutionary Optimization...

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20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2024

作者： Ye, Qiucheng Cai, Hongxia Bian, Yunqi School of Mechatronic Engineering and Automation Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China

ISBN: (纸本)9798350356328

Stable control of the iron-making process through the adjustment of operating parameters is essential to improve blast furnace productivity. However, due to the complex and dynamic nature of the reaction process, it is difficult to perform accurate modeling and simulation experiments for a blast furnace. This poses great difficulties in performing the evaluation of control strategies in real-time. Offline evolutionary optimization, as an optimization technique that relies only on historical data, enables the search for optimal operation parameters through the introduction of surrogates. Based on the characteristics of historical time-series data of the iron-making process, this study proposes an offline evolutionary optimization method based on advanced time-series surrogates. Ensemble strategy combining surrogates with different prediction time windows contributes robustness during the optimization process. Additionally, multiple sub-regions are maintained to enable extensive searching of the decision space with a multi-objective nature. The efficiency of the proposed pooling method is demonstrated through verification in actual production cases. © 2024 IEEE.

关键词： Blast furnaces

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Spatial Data Thickening-Based Carbon Nephogram Using UAV Real-Time Monitoring

Spatial Data Thickening-Based Carbon Nephogram Using UAV Rea...

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International Conference on Mechanical Design, ICMD 2023

作者： Nie, Zhiqi He, Bin Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9789819709212

This study explores the combination of unmanned aerial vehicle (UAV) and ground monitoring for real-time carbon footprint mapping technology in low-carbon smart parks. Addressing the conflict between sampling rate and monitoring efficiency in UAV monitoring, we propose a spatial data thickening algorithm based on moving window spline interpolation and time series fusion with inverse distance weighting. Meanwhile, a comprehensive carbon monitoring algorithm is proposed by combining ground and spatial carbon emission calculation methods. Furthermore, the concept of carbon nephogram is introduced to depict the spatial distribution and intensity of carbon emissions. By establishing an integrated monitoring system and conducting simulation experiments in a small-scale smart park scenario, the results show that the collaborative monitoring system has superiority in improving monitoring efficiency and affording intuitive insights. It provides an effective methodology for the intelligent design and maintenance of smart parks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Carbon footprint

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Motor test data quality evaluation model based on critic-fluctuant weight assignment method 3

Motor test data quality evaluation model based on critic-flu...

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2024 3rd International Conference on Electrical, Control and Information Technology, ECITech 2024

作者： Hu, Xiaomei Teng, Xianshu Hua, Yuting Weng, Jiahong The Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200072 China

The article addresses the limitations of traditional weight analysis methods in handling ground ignition experiment data for solid rocket motors, particularly the anti-interference ability to noise factors. To address this issue, the specialized Critic-Fluctuant weight analysis method is proposed. This method calculates objective weight values based on fluctuation values and integrates noise standard scores into data quality assessment, enabling researchers to effectively and intuitively identify different levels of data quality. After comparing and analyzing the objective weights and data quality scores of 100 ground ignition test data sets, it is verified that Critic-Fluctuant has higher adaptability and accuracy than traditional CRITIC methods in ground ignition test scenarios. The article provides new insights and tools for researchers to deal with similar data characteristics. © 2024 Published under licence by IOP Publishing Ltd.

关键词： Quality control

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Performance prediction method of solid rocket motor based on the ground test 4

Performance prediction method of solid rocket motor based on...

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2024 4th International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2024

作者： Hu, Xiaomei Hua, Yuting Weng, Jiahong Teng, Xianshu Zhang, Mingnan The Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200072 China

Solid rocket motor (SRM) is a core component of rockets. Considering the high cost of solid rocket motors and the high demand for transportation and storage, there is an urgent need to predict the performance of solid rocket motors before the ground ignition test to lower the cost of tests. Using data mining technology to predict various parameters of rocket motors with historical data has become a new development direction. In order to improve the data fitting effect and prediction accuracy, a novel prediction model was proposed, which tries to combine the Whale Optimization Algorithm (WOA) with the Error Correction Gated Recurrent Unit neural network (ECGRU) to correct the basic prediction performance of the Long Short-Term Memory neural network model (LSTM). Compared with traditional methods, experiments showed that the novel model was beneficial in improving the reliability of the prediction of the thrust and specific impulse. © Published under licence by IOP Publishing Ltd.

关键词： Long short-term memory

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Fault Diagnosis of Quadruped Robot Joint Modules Based on TDIC and Random Forest 5

Fault Diagnosis of Quadruped Robot Joint Modules Based on TD...

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5th International Conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2024

作者： Chen, Yufan Fan, Beibei Xiong, Xin Shi, Mapping School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China

ISBN: (纸本)9798331529192

As robotics technology advances, quadruped robots are increasingly instrumental in diverse applications, including rescue operations and healthcare. However, the intricate operating conditions expose the components within the joint modules of these robots to alternating and impact loads. Consequently, research into signal processing and fault diagnosis techniques for planetary gearboxes in joint modules holds significant engineering importance. Given the challenges associated with fault signal extraction from planetary gearboxes, this study proposes a novel fault feature extraction method based on Time-Dependent Intrinsic Correlation (TDIC), integrated with a random forest classifier for fault classification. This approach leverages signal frequency analysis to adaptively extract segments characterized by high correlation among different physical field signals as fault features. The random forest model is utilized for fault classification and its performance is compared against CNN, KNN, and XGBoost models. Experimental results validate the superior fault classification efficacy of the proposed method. © 2024 IEEE.

关键词： Multipurpose robots

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