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Multi-agent reinforcement learning method for cutting parameters optimization based on simulation and experiment dual drive environment Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-30 Weiye Li, Caihua Hao, Songping He, Chaochao Qiu, Hongqi Liu, Yanyan Xu, Bin Li, Xin Tan, Fangyu Peng
Improving production efficiency while ensuring product surface quality is a constant focus of manufacturers. Cutting parameter optimization is an important technique for ensuring high-efficiency and high-quality production. In this paper, a novel method for cutting parameter optimization that integrates multi-agent reinforcement learning with a dual-drive virtual machining environment is proposed.
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Electroelastic wave dispersion in the rotary piezoelectric NEMS sensors/actuators via nonlocal strain gradient theory Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-30 Yuan Guo, Allam Maalla, Mostafa Habibi, Zohre moradi
This article introduces a computational means for investigating the electroelastic nonlinear wave dispersion traits of the nano-dimension sandwich pipe, which is composed of a core formed of a bi-directional functionally graded (Bi-FG) material, together with a piezoelectric sensor/actuator. A combination of Hamilton’s principle, first-order shear deformation, along with Von-Karman nonlinearity, is
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Efficiency comparison of MCMC and Transport Map Bayesian posterior estimation for structural health monitoring Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-30 Jan Grashorn, Matteo Broggi, Ludovic Chamoin, Michael Beer
In this paper, an alternative to solving Bayesian inverse problems for structural health monitoring based on a variational formulation with so-called transport maps is examined. The Bayesian inverse formulation is a widely used tool in structural health monitoring applications. While Markov Chain Monte Carlo (MCMC) methods are often implemented in these settings, they come with the problem of using
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A novel mode coupling mechanism for predicting low-frequency chatter in robotic milling by providing a vibration feedback perspective Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-30 Jiawei Wu, Xiaowei Tang, Fangyu Peng, Rong Yan, Shihao Xin
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Calculation and Analysis of Motor Dynamic Stress Considering Multiphysical Field Loads for In-Wheel Electric Vehicle Applications IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-30 Di Tan, Fang Qiu, Huiting Han, Zhangji Pang
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A multi-band elastic metamaterial for low-frequency multi-polarization vibration absorption Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-29 Shiteng Rui, Weiquan Zhang, Rihuan Yu, Xingzhong Wang, Fuyin Ma
The vibration of engineering structures in actual practice occurs across numerous frequency ranges and includes diverse polarization modes such as bending, torsion, and expansion. Nevertheless, most reported elastic metamaterials are designed for a single frequency range or a single elastic wave mode, thereby making it challenging to simultaneously suppress the propagation of vibrational energy across
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Mesh stiffness calculation of defective gear system under lubrication with automated assessment of surface defects using convolutional neural networks Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-29 Siyu Wang, Penghao Duan
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Multileader and Role-Based Time-Varying Formation Using GP Inference and Sliding-Mode Control IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-29 Ryan Adderson, Behzad Akbari, Ya-Jun Pan, Haibin Zhu
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Twist compensated, high accuracy and dynamic fiber optic shape sensing based on phase demodulation in optical frequency domain reflectometry Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-27 Sheng Li, Qingrui Li, Zhenyang Ding, Kun Liu, Huafang Wang, Peidong Hua, Haohan Guo, Teng Zhang, Ji Liu, Junfeng Jiang, Tiegen Liu
We present a twist compensated, high accuracy and dynamic fiber optic shape sensing based on phase demodulation in Optical Frequency Domain Reflectometry (OFDR) by using multiple single core fiber based sensor (MFS). A dynamic strain sensing is realized by tracking the optical phase in OFDR and combining with the phase de-hopping filtering algorithm, and the sensing spatial resolution reaches 45 μm
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A Bayesian network development methodology for fault analysis; case study of the automotive aftertreatment system Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-27 Morteza Soleimani, Sepeedeh Shahbeigi, Mohammad Nasr Esfahani
This paper proposes a structured methodology for generating a Bayesian network (BN) structure for an engineered system and investigates the impact of integrating engineering analysis with a data-driven methodology for fault analysis. The approach differs from the state of the art by using different initial information to build the BN structure. This method identifies the cause-and-effect relationships
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Frequency response function-based closed-form expression for multi-damage quantification and its application on shear buildings Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-27 Saranika Das, Koushik Roy
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Optimal weight impulse extraction: New impulse extraction methodology for incipient gearbox condition monitoring Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-27 Xiaofei Liu, Naipeng Li, Yaguo Lei, Dong Wang, Qubing Ren, Jinze Jiang, Yuan Wang
Gear faults in a transmission system generally cause impulse components in vibration signals, which is a crucial symbol for gearbox fault diagnosis. However, their related signals are often interfered or even submerged by the noisy meshing components (NMC) of gearboxes in degradation, which introduces challenges for incipient fault detection and condition monitoring. Commonly employed deconvolution-based
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Floating offshore wind turbine mooring line sections health status nowcasting: From supervised shallow to weakly supervised deep learning Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-27 Andrea Coraddu, Luca Oneto, Jake Walker, Katarzyna Patryniak, Arran Prothero, Maurizio Collu
The global installed capacity of floating offshore wind turbines is projected to increase by at least 100 times over the next decades. Station-keeping of floating offshore renewable energy devices is achieved through the use of mooring systems. Mooring systems are exposed to a variety of environmental and operational conditions that cause corrosion, abrasion, and fatigue. Regular physical in-service
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Meta-learning-based approach for tool condition monitoring in multi-condition small sample scenarios Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-27 Bowen Zhang, Xianli Liu, Caixu Yue, Steven Y. Liang, Lihui Wang
Tool Condition Monitoring (TCM) technology in machining is crucial for maintaining safety and optimizing costs. However, its practical application faces two significant challenges: difficulties in data collection and a decline in generalization performance across different monitoring tasks. To this end, a hybrid feature boundary-enhanced meta-learning network with adaptive gradients (HFBEAML) is proposed
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Enhanced selective delayless subband algorithm independent of primary disturbance configuration for multi-channel active noise control system in vehicles Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-26 Xiaolong Li, Chihua Lu, Wan Chen, Zhien Liu, Can Cheng, Yongliang Wang, Songze Du
The selective delayless subband structure stands out as a promising algorithmic choice for the multi-channel active control of vehicle interior noise, particularly in the context of road noise. This type of algorithm reduces the eigenvalue spread of the autocorrelation matrix of the signal by decomposing the signal into subbands, and the desired subbands are activated selectively, thus achieving a
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An MFC-based friction damper with adjustable normal force: conception, modelling, and experiment Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-26 Y.G. Wu, J.B. Chen, Y. Fan, L. Li, Z. Jiang
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A Modular Soft Pipe-Climbing Robot With High Maneuverability IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-26 Wenbiao Wang, Xin Wang, Gang Zheng, Rui Chen, Zean Yuan, Jincheng Huang, Ke Wu, Guanjun Bao
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Interest Point Selection and Feature Extraction in Six-DoF Grasp Pose Detection IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-26 Rui He, Haoyao Chen, Mengmeng Fu
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An Adaptive UKF for Vehicle State Estimation With Delayed Measurements and Packet Loss IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-26 Shuo Bai, Jingyu Hu, Yongjun Yan, Dawei Pi, Haonan Ding, Lilin Shen, Guodong Yin
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A Wearable Human–Machine-Interface (HMI) System Based on Colocated EMG-pFMG Sensing for Hand Gesture Recognition IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-26 Shen Zhang, Hao Zhou, Rayane Tchantchane, Gursel Alici
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A High-Performance piezoelectric micropump designed for precision delivery Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-25 Meng Wang, Luntao Dong, Runyu Liu, Conghui Wang, Xiaodong Sun, Xinbo Li, Guojun Liu, Zhigang Yang
A piezoelectric micropump (PE pump) was proposed featuring a multi-plate cantilever valve (MPCV) and a ramp channel (RC) to deliver high performance in a compact design. Both the MPCV and RC underwent thorough theoretical, simulation-based, and experimental evaluations. A specialized driver plate was then developed to precisely control the PE pump. Key parameters of the PE pump were optimized based
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Wide quasi-zero stiffness region isolator with decoupled high static and low dynamic stiffness Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-25 Wenjun Shi, Weiqun Liu, Chunrong Hua, Hongkun Li, Qiao Zhu, Dawei Dong, Yanping Yuan
Quasi-zero stiffness (QZS) isolators can achieve the two goals of relatively high static and low dynamic stiffness (HSLDS). However, the static and dynamic stiffness of most QZS isolators remains coupled, causing conflicts in optimizing these dual objectives, especially in the case of large displacement excitations and heavy loads, leading to limited performance. To overcome these limitations, this
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Experimental comparison of three automatic operational modal analysis algorithms on suspension and floating bridges Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-25 Anno Christian Dederichs, Gunnstein T. Frøseth, Ole Øiseth
Automatic operational modal analysis is necessary for long-term monitoring of structures when using modal information. Many algorithms have been proposed to accomplish this task; two examples are the fully automatic algorithm by Reynders et al. in 2012 and the semi-automatic algorithm by Kvåle and Øiseth in 2020; however, few in-depth direct comparisons exist. This work compares the two algorithms
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A CNN-BiLSTM-Attention approach for EHA degradation prediction based on time-series generative adversarial network Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-25 Zhonghai Ma, Yiwen Sun, Hui Ji, Suolan Li, Songlin Nie, Fanglong Yin
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Damping prediction of highly dissipative meta-structures through a wave finite element methodology Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-25 Dongze Cui, Noureddine Atalla, Mohamed Ichchou, Abdel-Malek Zine
Aiming at accurately predicting the global Damping Loss Factor (DLF) for Highly Dissipative Structures (HDS), the current study uses the Wave Finite Element (WFE) methodology. It starts by deriving the forced responses of a Unit Cell (UC) representative of the periodic meta-structure. Then it computes the DLF of the wave via the power balance. The Bloch expansion is employed. The response to a point
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Why animals can outrun robots Sci. Robot. (IF 25.0) Pub Date : 2024-04-24 Samuel A. Burden, Thomas Libby, Kaushik Jayaram, Simon Sponberg, J. Maxwell Donelan
Animals are much better at running than robots. The difference in performance arises in the important dimensions of agility, range, and robustness. To understand the underlying causes for this performance gap, we compare natural and artificial technologies in the five subsystems critical for running: power, frame, actuation, sensing, and control. With few exceptions, engineering technologies meet or
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Learning robust autonomous navigation and locomotion for wheeled-legged robots Sci. Robot. (IF 25.0) Pub Date : 2024-04-24 Joonho Lee, Marko Bjelonic, Alexander Reske, Lorenz Wellhausen, Takahiro Miki, Marco Hutter
Autonomous wheeled-legged robots have the potential to transform logistics systems, improving operational efficiency and adaptability in urban environments. Navigating urban environments, however, poses unique challenges for robots, necessitating innovative solutions for locomotion and navigation. These challenges include the need for adaptive locomotion across varied terrains and the ability to navigate
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Shear localization-induced amorphization in nanocrystals during high strain rate deformation Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-04-24 Qi-lin Xiong, Takahiro Shimada, Takayuki Kitamura
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Engineering Compliance in Legged Robots Via Robust Co-Design IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-24 Gabriel Bravo-Palacios, He Li, Patrick M. Wensing
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Full-field displacement measurement of long-span bridges using one camera and robust self-adaptive complex pyramid Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-23 Yuchao Wang, Weihua Hu, Jun Teng, Yong Xia
Full-field motion with a high spatial resolution can reflect the health state of long-span bridges. Traditional structural health monitoring (SHM) systems measure the structural displacement at sparse points only. Despite the development of various methods for obtaining high-resolution responses, they fail to estimate the multi-scale motions of real long-span bridges. A novel full-field motion estimation
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The assignment of zero sound pressure frequencies using measured sound pressure receptances and structural receptances Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-23 Yingsha Shi, Sheng Li
In structural receptances, the zeros (antiresonances) define those frequencies at which vibrations disappear. In this paper, the zero sound pressure frequency is defined as the frequency at which the sound pressure is zero at certain locations. A method for the assignment of zero sound pressure frequencies using measured sound pressure receptances and structural receptances is proposed through two
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Physics-based prognostics of rolling-element bearings: The equivalent damaged volume algorithm Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-23 Alberto Gabrielli, Mattia Battarra, Emiliano Mucchi, Giorgio Dalpiaz
This paper introduces a novel parameter related to bearing degradation, namely the Equivalent Damaged Volume (EDV). An algorithm capable of extracting EDV values from experimental data is detailed. To this end, the proposed technique relies on the comparison between experimental and numerical signals. The former are the result of an extensive campaign of run-to-failure tests performed on a dedicated
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rLSTM-AE for dimension reduction and its application to active learning-based dynamic reliability analysis Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-23 Yu Zhang, You Dong, Michael Beer
A novel method termed rLSTM-AE is developed for the low-dimensional latent space identification of the stochastic dynamic systems with more than 1000 input random variables and the active learning-based dynamic reliability analysis. First, the long short-term memory network considers both the time-variant stochastic excitation and the time-invariant random variables is developed (rLSTM), which adopts
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Tracking superharmonic resonances for nonlinear vibration of conservative and hysteretic single degree of freedom systems Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-23 Justin H. Porter, Matthew R.W. Brake
Many modern engineering structures exhibit nonlinear vibration. Characterizing such vibrations efficiently is critical to optimizing designs for reliability and performance. For linear systems, steady-state vibration occurs only at the forcing frequencies. However, nonlinearities (e.g., contact, friction, large deformation, etc.) can result in nonlinear vibration behavior including superharmonics —
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Estimating structural motions in extreme environmental conditions——A dynamic correlation filter based computer vision approach Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-23 Enjian Cai, Yi Zhang, Xinzheng Lu, Xiaodong Ji, Xiang Gao, Jiale Hou, Ji Shi, Wei Guo
Vision-based methods have shown great potential in vibration-based structural health monitoring (SHM). However, these methods are not standard practices yet, since their accuracy and robustness may be influenced by extreme environmental conditions. To this end, this paper proposed a method, named dynamic regularized total variation correlation filter (DTVCF). In DTVCF, an effective optimization problem
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Failure analysis of bolted steel plate connections with three-dimensional flexibilities Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-04-23 D.A. Abdoh
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Physical Human–Robot Interaction Based on Adaptive Impedance Control for Robotic-Assisted Total Hip Arthroplasty IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-23 Yiming Chen, Yuhao Zhang, Xingwei Zhao, Qiang Xie, Kun Yang, Bo Tao, Han Ding
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A Novel Variable Stiffness Actuator Based on Cable-Pulley-Driven Mechanisms for Robotics IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-23 Zhisen Li, Peng Xu, Bing Li
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Robust Precision Motion Control Based on Enhanced Unknown System Dynamics Estimator for High-DoF Robot Manipulators IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-23 Xinyu Jia, Jun Yang, Tian Shi, Wenxin Wang, Yongping Pan, Haoyong Yu
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MGLT: Magnetic-Lead Global Localization and Tracking in Degenerated Repetitive Environments IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-23 Zhenyu Wu, Wei Wang, Jun Zhang, Yuanzhe Wang, Guohao Peng, Danwei Wang
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Iterative Learning for Gravity Compensation in Impedance Control IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-23 Teng Li, Amir Zakerimanesh, Yafei Ou, Armin Badre, Mahdi Tavakoli
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Experimental nonlinear model of a set of connecting elements in view of nonlinear modal coupling Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-22 Jacopo Brunetti, Walter D’Ambrogio, Annalisa Fregolent, Francesco Latini
The development process of mechanical systems involves the evaluation of its modes of vibrations in the frequency range of interest. In general, a linear modal analysis is sufficient to determine whether the system can operate in dynamic conditions. However, in some cases the assembly is composed of many subsystems connected through nonlinear connections which make the response depend on the amplitude
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Neurosymbolic Motion and Task Planning for Linear Temporal Logic Tasks IEEE Trans. Robot. (IF 7.8) Pub Date : 2024-04-22 Xiaowu Sun, Yasser Shoukry
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Soft Printable Robots with Flexible Metal Endoskeleton IEEE Trans. Robot. (IF 7.8) Pub Date : 2024-04-22 Chao-Yu Chen, Benjamin W.K.Ang, Yangfan Li, Jun Liu, Zhuangjian Liu, Chen-Hua Yeow
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Autonomous Vehicle Localization Without Prior High-Definition Map IEEE Trans. Robot. (IF 7.8) Pub Date : 2024-04-22 Sangmin Lee, Jee-Hwan Ryu
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Online Multi-Contact Receding Horizon Planning via Value Function Approximation IEEE Trans. Robot. (IF 7.8) Pub Date : 2024-04-22 Jiayi Wang, Sanghyun Kim, Teguh Santoso Lembono, Wenqian Du, Jaehyun Shim, Saeid Samadi, Ke Wang, Vladimir Ivan, Sylvain Calinon, Sethu Vijayakumar, Steve Tonneau
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Heterogeneous Targets Trapping With Swarm Robots by Using Adaptive Density-Based Interaction IEEE Trans. Robot. (IF 7.8) Pub Date : 2024-04-22 Shuai Zhang, Xiaokang Lei, Xingguang Peng, Jia Pan
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Complete and Near-Optimal Robotic Crack Coverage and Filling in Civil Infrastructure IEEE Trans. Robot. (IF 7.8) Pub Date : 2024-04-22 Vishnu Veeraraghavan, Kyle Hunte, Jingang Yi, Kaiyan Yu
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On the Generality and Application of Mason's Voting Theorem to Center of Mass Estimation for Pure Translational Motion IEEE Trans. Robot. (IF 7.8) Pub Date : 2024-04-22 Ziyan Gao, Armagan Elibol, Nak Young Chong
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Parallel Manipulator Double Stage Calibration Based on Adaptive Kalman Filter IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-22 Omid Mahdi Zadeh, Vahid Akbari, S. Ali A. Moosavian, Esmaeil Najafi
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Task Optimization for a Class of Mobile Depth Sensor Network in Unknown Environments IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-04-22 Zike Lei, Xi Chen, Ying Tan, Xiang Chen, Li Chai
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Compressible FSI of elastic spikes for drag reduction under hypersonic flow Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-04-21 Wen-Fan Wang, Mei Mei, Zhi-Qiao Wang, Zhi-Fu Zhou, Wei-Tao Wu
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Finite deformation micropolar peridynamic theory: Variational consistency of wryness measure Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-04-21 Sajal, Pranesh Roy
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Laser shock-enabled optical–thermal–mechanical coupled welding method for silver nanowires Int. J. Mach. Tool Manu. (IF 14.0) Pub Date : 2024-04-20 Yizhong Hu, Xiaohan Zhang, Hongtao Ding, Yaowu Hu
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How does the uncut chip thickness affect the deformation states within the primary shear zone during metal cutting? Int. J. Mach. Tool Manu. (IF 14.0) Pub Date : 2024-04-20 Kai Ma, Zhanqiang Liu, Bing Wang, Qinghua Song, Yukui Cai
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Partially observable deep reinforcement learning for multi-agent strategy optimization of human-robot collaborative disassembly: A case of retired electric vehicle battery Robot. Comput.-Integr. Manuf. (IF 10.4) Pub Date : 2024-04-20 Jiaxu Gao, Guoxian Wang, Jinhua Xiao, Pai Zheng, Eujin Pei
The burgeoning electric vehicle (EV) industry has precipitated a commensurate surge in the consumption of EV batteries, which are currently labor-intensive and inefficient for the recycling and disassembly of EV batteries. However, it is a potential trend to enhance the efficacy and safety of the disassembly of EV batteries based on human-robot collaboration (HRC) method. Because of the uncertainty
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On-machine measurement and compensation of thin-walled surface Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-04-20 Lida Zhu, Yanpeng Hao, Shaoqing Qin, Xiaoyu Pei, Tianming Yan, Qiuyu Qin, Hao Lu, Boling Yan, Xin Shu, Jianhua Yong
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Geometric deviation during incremental sheet forming process: Analytical modeling and experiment Int. J. Mach. Tool Manu. (IF 14.0) Pub Date : 2024-04-19 Zhidong Chang, Mei Yang, Jun Chen
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Reliable arrival time picking of acoustic emission using ensemble machine learning models Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-19 Xiao Wang, Qingrui Yue, Xiaogang Liu
This study presents an innovative method for accurately picking the first-wave arrival time in acoustic emission (AE) localization, particularly effective in environments with low or variable signal-to-noise ratios (SNR). Utilizing an ensemble learning model, it synergizes multiple automatic arrival time estimation algorithms to enhance both consistency and robustness. The model, rooted in decision
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Multiscale fluid–structure coupled real-time hybrid simulation of monopile wind turbines with vibration control devices Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-04-19 Hao Ding, Zili Zhang, Jinting Wang, Jian Zhang, Okyay Altay