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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Toothman, Maxwell Braun, Birgit Bury, Scott J. Moyne, James Tilbury, Dawn M. Barton, Kira University of Michigan Department of Mechanical Engineering Ann ArborMI48109 United States The Dow Chemical Company MidlandMI48674 United States University of Michigan Department of Robotics Ann ArborMI48109 United States

ISBN: (纸本)9798350320695

Predictive modeling of industrial rotating equipment is difficult due to a number of implementation challenges. Existing approaches are not well-equipped to adapt to the range of degradation trends that industrial equipment experience and typically depend on large historical datasets for model training. In this paper, a state-based framework for modeling multi-stage degradation in rotating equipment is introduced. With this approach, machine experts can define multi-stage models of equipment health based on first principles or pre-existing knowledge in place of extensive historical data. An adaptive methodology is presented to estimate a machine's health stage history and predict faults based on real-time sensor measurements. A case study with rolling element bearings shows that the proposed approach makes fault predictions with similar accuracy rates as data-driven models trained on multiple historical faults while providing additional degradation detection capabilities. © 2023 IEEE.

关键词： Large dataset

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Development of a Vibration-driven Capsule Robot with Protruding Magnetic Bristles with Enhanced Adaptability in Wet and Dry Environments

Development of a Vibration-driven Capsule Robot with Protrud...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Zhang, Yujie Wei, Tanyong He, Shujing Hong, Yuying Hu, Chengzhi Southern University of Science and Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Shenzhen518055 China Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9798350325706

Colonoscopy is a widely used method for diagnosing bowel cancers, requiring coordinated efforts from medical professionals due to its invasive nature. In contrast, miniature capsule robots, measuring just a few centimeters, offer a less invasive diagnostic option by integrating multiple functions. However, current capsule robots face challenges with complex designs, limited mobility, size, and cost, which hinder their adoption and reduce gastrointestinal disorder screening rates. To address these issues, we introduce the vibration-driven capsule robot (VCR) with magnetic protruding bristle structures. Four simple components (shell structure, electronic components, permanent magnet, and magnetic soft bristles) are designed to improve the robot's mobility in dry and wet environments. The magnetic bristle structures are inspired by flexible organisms and enhance the robot's adaptability. The robot is propelled by centrifugal force from a vibration motor, allowing efficient movement along the intestinal tract while protecting the patient's lining. The fabrication process of the magnetic soft bristles has been refined to optimize material ratios and enhance the robot's performance. The vibration motor's output is analyzed using load cells to ensure efficiency. For precise path planning, an external permanent magnet (EPM) is applied to guide the capsule's direction. Experiments confirm the VCR's versatility, performing fluid linear and curved motions in different environments. These findings underscore the feasibility of the VCR as a potent tool for non-invasive, timely screening of gastrointestinal disorders. © 2023 IEEE.

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Image Stitching in Neutron Radiography for Surface Extraction of Additively Manufactured Parts

Image Stitching in Neutron Radiography for Surface Extractio...

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2023 Transactions of the American Nuclear Society Annual Meeting and Technology Expo, ANS 2023

作者： Bisbee, Matthew Oksuz, Ibrahim Harke, Kathryn Cherepy, Nerine Townsend, Andrew Cao, Lei R. Nuclear Engineering Program Department of Mechanical and Aerospace Engineering The Ohio State University United States AwareAbility Technologies LLC Lawrence Livermore National Laboratory United States Nuclear Reactor Laboratory The Ohio State University United States

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Humans and Their Dogs’ Pesticide Air Exposure Concentrations in Boulder Colorado Using Passive Wearable Monitors 18

Humans and Their Dogs’ Pesticide Air Exposure Concentration...

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18th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Hollo, Aniya Khalili Johnson, Emily Lin, Elizabeth Z. Abernathy, Rella Godri Pollitt, Krystal J. Miller, Shelly L. Department of Mechanical Engineering University of Colorado Boulder80309 United States Environmental Engineering Program University of Colorado Boulder80309 United States Department of Environmental Health Sciences Yale School of Public Health New HavenCT06520 United States Department of Climate Initiatives City of Boulder BoulderCO80302 United States

ISBN: (纸本)9798331306816

Pesticide use in urban areas has human health and environmental impacts. The objective of this study was to assess the inhalation exposure of domestic dogs and their owners to pesticides. Dogs were studied due to their exposure to a range of sources, they breathe close to the ground where pesticides are applied, and they bring chemicals inside. The exposure of 38 human adult and dog pairs in Boulder County, Colorado, US was evaluated in October and November 2022, during the non-peak season for lawn chemical application, using wearable passive samplers. Fresh Air polydimethylsiloxane samplers were attached to the dogs’ collar and their owners wore wristband samplers. Pesticides concentrations were assessed by gas chromatography high-resolution mass spectrometry using targeted and non-targeted analyses. Nine of the 15 legacy pesticides included in the targeted panel were detected. Three of these compounds were detected in all human and dog samples (N-nitrosodiphenylamine (100% detection frequency), 4-nitroan-iline (92%), and 4-chloroaniline (82%)). Despite being banned in the US, dichlorodiphenyltrichloroethane (DDT), was detected in two humans and one dog. Exposure concentrations for four out of six chemicals detected in human samples were above the 10-6 US Environmental Protection Agency’s acceptable cancer risk level. © 2024 18th Conference of the International Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - Conference program and Proceedings. All rights reserved.

关键词： Gas chromatography

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An Enhancement of the Computational Efficiency of Parametric Component Mode Synthesis Within Limited Parameter Domains Using Conventional Interpolations

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Multiscale Science and engineering 2022年第1期4卷 66-72页

作者： Lee, Jaehun Department of Mechanical Robotics and Energy Engineering Dongguk University Seoul Republic of Korea

This paper presents the usages of conventional interpolation functions for interpolation-based parametric component mode synthesis (IB-PCMS) method within limited parameter domains. One of the representatives of reduced-order models (ROM) is the one using the offline-online strategy, which constructs multiple ROMs at given sampling points in the offline stage and manipulates them to derive a ROM at the new query point in the online stage efficiently via, for example, using the interpolation of the constructed ROMs. For such a process in the online stage, manifold interpolations, congruence transformations, and the mode exclusion steps are required to guarantee the accuracy and the robustness of the ROM, which complexifies computational procedures in the offline stage. For the cases where the design parameters do not change dramatically due to the limited domain of interest, and as a result, if the ROM does not experience any mode veering phenomena, simple interpolations can guarantee accurate solutions. The validities of using conventional interpolations are investigated for a numerical example providing the assessments of the accuracy for representative interpolation functions.

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Learning Complicated Manipulation Skills Via Deterministic Policy with Limited Demonstrations

Learning Complicated Manipulation Skills Via Deterministic P...

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International Conference on Advanced robotics (ICAR)

作者： Haofeng Liu Jiayi Tan Yiwen Chen Marcelo H Ang Department of Mechanical Engineering National University of Singapore Advanced Robotics Centre College of Design and Engineering National University of Singapore

Deep reinforcement learning, when combined with demonstrations, can effectively formulate policies for manipulators. However, the practical collection of ample high-quality demonstrations is time-consuming, and demonstrations generated by humans may not perfectly correspond with the operational demands of robots. These challenges are intensified by issues such as non-Markovian processes and excessive reliance on demonstrations. Our study indicates that in manipulation tasks, reinforcement learning (RL) agents are sensitive to the quality of demonstrations and struggle to adapt to those derived from humans. As a result, leveraging low-quality or scarce demonstrations to assist reinforcement learning in developing superior policies presents a significant challenge. In some cases, dependence on limited demonstrations may paradoxically impair performance. To address these challenges, we propose a novel algorithm, TD3fG (TD3 learning from a generator). This algorithm facilitates a seamless transition from learning from experts to learning from experience, enabling agents to assimilate prior knowledge while mitigating the negative impacts of the demonstrations. Our algorithm demonstrates notable improvement in the Adroit manipulator and MuJoCo tasks, even with limited demonstrations of mixed failure trajectory.

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Vibration Energy Harvesting: A Review on Trends, Challenges & Future Direction 5

Vibration Energy Harvesting: A Review on Trends, Challenges ...

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5th IEEE International Conference on Electro-Computing Technologies for Humanity, NIGERCON 2024

作者： Afolalu, Sunday A. Ogedengbe, Temitayo S. Emetere, Moses E. Monye, Stella I. Snow, Monye N. Afe Babalola University Dept. of Mechanical and Mechatronics Engineering Ado-Ekiti Nigeria University Johannesburg Dept. of Mechanical Science South Africa Nile University of Nigeria Dept. of Mechanical Engineering Department Abuja Nigeria Bowen University Dept. of Physics Program Osun State Iwo Nigeria University of Delta Dept. of Information Communication Technology Delta State Agbor Nigeria

ISBN: (纸本)9798331542559

The worldwide need for sustainable energy solutions has continued to attract the attention of researchers. One vital means for such provision is the harvesting of energy using various methods. This study therefore reviews the recent trends in energy harvesting. Methods such as vibration energy harvesting as well as electrostatic energy harvesting and their applications have been thoroughly discussed. The study also reviewed the challenges with this energy harvesting methods and finally concludes with the future directions of this topic. It is believed that the generation of energy if greatly boosted will drive the economy of any state and ultimately result in wealth generation for the economy. © 2024 IEEE.

关键词： Energy Generation Harvesting Power Vibration

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Dimensionless Analysis of the Transition from Continuous Jet Mode to Natural Pulsation in Electrohydrodynamic Jet Printing

Dimensionless Analysis of the Transition from Continuous Jet...

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2023 IEEE Conference on Control Technology and Applications, CCTA 2023

作者： Bahrami, Ali Hawa, Angelo Yue, Kaifan Barton, Kira University of Michigan Mechanical Engineering Department 2350 Hayward St. Ann ArborMI48109 United States University of Michigan Department of Robotics 2505 Hayward St. Ann ArborMI48109 United States

ISBN: (纸本)9798350335446

Electrohydrodynamic jet (e-jet) printing is a promising additive manufacturing technique that has demonstrated high-resolution fabrication capabilities. Various jetting regimes as a function of the input voltage signal have been identified and studied. In DC printing, a transition has been observed from the continuous jet to the natural pulsation mode, which precipitates less predictable outcomes on the print rate and quality of the final pattern. This phenomenon is not well understood, and its behavior is yet to be characterized. Accordingly, the natural pulsation initiation (NPI) of 15 solutions with unique viscosities and conductivities was analyzed. Dimensionless parameters referencing material properties (Ohnesorge and ratio of capillary to charge relaxation time), applied voltage (electric capillary), and induced flow rate (Weber) are implemented to analyze the dynamics of this transition. Our findings indicate that NPI is generally more prevalent in inks with higher conductivities. Additionally, less viscous inks appeared to inhibit NPI, providing a larger design space for attaining stable behavior. © 2023 IEEE.

关键词： Electrohydrodynamics

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Multidisciplinary Control Co-Design Optimization of Anguilliform-Swimming Soft Fluidic Robots

Multidisciplinary Control Co-Design Optimization of Anguilli...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Andrew Fletcher Ru Xiang Luca Scotzniovsky Jacobo Cervera-Torralba Michael T. Tolley John T. Hwang Department of Mechanical and Aerospace Engineering Materials Science and Engineering Program University of California San Diego (UCSD) La Jolla CA USA

ISBN: (数字)9798331520205

ISBN: (纸本)9798331520212

Anguilliform-swimming soft fluidic robots hold great promise for a range of underwater applications. However, because they leverage the complex dynamics of soft bodies interacting with fluids, it is challenging to use intuition to determine design parameters. Multidisciplinary design optimization offers a promising solution to this challenge by providing an automated and systematic method for leveraging computational models to find optimal design parameters. This study investigates a method for multidisciplinary control co-design optimization of anguilliform-swimming soft robots, using physics-based models to optimize shape and control parameters. The modeling framework includes a geometry-centric approach for geometry modeling and parameterization, a three-dimensional finite element model for structural mechanics, and an unsteady panel method for fluid dynamics. The approach is tested by applying it to the optimization of a pre-existing eel-inspired soft robot. Model parameters are estimated from existing experimental data, and two control co-design optimizations, with high-level and multilevel shape parameterizations, are performed to minimize energy cost. The optimized actuator module is manufactured, and used to collect additional data for re-estimating the structural model parameters. The optimization is performed again with the updated model parameters, showing a simulated energy cost reduction of 45% and the prescribed 128% speed increase compared to the baseline design with optimized control and updated model parameters. These results demonstrate the potential of the proposed optimization approach to advance the performance of anguilliform-swimming soft fluidic robots.

关键词： Geometry Solid modeling Costs Shape Computational modeling Fluid dynamics Soft robotics Data models Manufacturing Optimization

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Distributed operational management of microgrids: a second order dual update approach

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IFAC-PapersOnLine 2023年第2期56卷 1540-1545页

作者： Giulio Ferro Michela Robba Federico Delfino Rabab Haider Anuradha M. Annaswamy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA 02141 USA Department of of Electrical Electronic Telecommunications Engineering and Naval Architecture University of Genova

This paper develops a Distributed Energy Management System (EMS) to optimally allocate electric and thermal power production in a polygenerative microgrid. The EMS problem is formulated as a multiperiod convex optimization problem and solved using AL-SODU, a new distributed algorithm based on the augmented Lagrangian method with second order dual updates. The proposed AL-SODU algorithm significantly outperforms state of the art algorithms employing first order dual updates, with 15-times speedup in convergence speed. A case study of the EMS based on AL-SODU is conducted on the Smart Polygeneration Microgrid (SPM) located on the Savona Campus of University of Genova (Italy). The EMS determines the optimal schedules for electric and thermal power plants every 15-minutes. This real time scheduling of the microgrid is enabled by the Al-SODU algorithm, which solves the scheduling problem in 1.86s.

关键词： Microgrids distributed control second order methods

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