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On population-based structural health monitoring for bridges: Comparing similarity metrics and dynamic responses between sets of bridges Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-09 Andrew Bunce, Daniel S. Brennan, Alan Ferguson, Connor O'Higgins, Su Taylor, Elizabeth J Cross, Keith Worden, James Brownjohn, David Hester
Bridges are valuable infrastructure assets that are challenging and expensive to maintain. State-of-the-art data-based bridge SHM solutions look to use bridge response data for condition assessment and damage detection. Data-based SHM methods can be limited in their application as they require large datasets to train models effectively, and most bridges lack the available data for the approaches to
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Transmissibility-based operational modal analysis: A unified scheme and uncertainty quantification Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-09 Jie Kang, Jiabao Sun, Jie Luo, Xiaoteng Liu
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MTGrasp: Multiscale 6-DoF Robotic Grasp Detection IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-05-09 Sheng Yu, Di-Hua Zhai, Yuanqing Xia
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Topology optimization of AISI 4140 steel with surface texture filled by multi-solid lubricants for enhancing tribological properties Friction (IF 6.8) Pub Date : 2024-05-07 Qipeng Huang, Chaohua Wu, Xiaoliang Shi, Kaipeng Zhang
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Anisotropic tribology and electrification properties of sliding-mode triboelectric nanogenerator with groove textures Friction (IF 6.8) Pub Date : 2024-05-07 Weixu Yang, Jieyang Wang, Xiaoli Wang, Ping Chen
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High-speed bearing diagnostics: Observations from the Surveillance 8 Safran contest data Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-08 Wade A. Smith, Pietro Borghesani, Robert B. Randall, Jérôme Antoni, Mohammed El Badaoui, Zhongxiao Peng
It is usually assumed that faulty bearings produce second-order cyclostationary (CS2) signals, and thus the natural process for their diagnostic analysis involves first the removal of first-order cyclostationary (CS1) components, such as from gears, followed by amplitude demodulation of an ‘informative’ frequency band, and subsequent envelope analysis, in which the spectrum of the (squared) envelope
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Time series diffusion method: A denoising diffusion probabilistic model for vibration signal generation Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-08 Haiming Yi, Lei Hou, Yuhong Jin, Nasser A. Saeed, Ali Kandil, Hao Duan
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Identification of linear flat outputs using neural networks—Examples of two-degree-of-freedom underactuated mechanical systems Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-08 Shangjie Frank Ma, Anni Zhao, Jian-Qiao Sun
This paper proposes a neural networks-based approach of finding flat output of linearized underactuated mechanical systems (UMS). Given that differential flatness and controllability are equivalent for linear systems, the problem is equivalent to finding the Brunovsky canonical form of linearized UMSs. We use a two degree-of-freedom (2DOF) system to illustrate the theoretical development. The proposed
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Dissipative Leaderless Formation via Nonfragile Memory Sampled-Data Control for Unmanned Surface Vehicles With Switching Topologies IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-05-08 Xiangli Jiang, Guihua Xia
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Dynamic error prediction and link strain feedback control for a novel heavy load multi-DOF envelope forming machine Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-07 Fangyan Zheng, Xinghui Han, Lin Hua, Wuhao Zhuang, Bo Huang
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Blade Profile Reconstruction via Multiview Registration Based on Bidirectional Correspondence and Global Distance Weight IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-05-07 Jie Dong, Zongping Wang, Luofeng Xie, Guofu Yin
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Model-Data Hybrid Driven Control of Hydraulic Euler–Lagrange Systems IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-05-07 Zhikai Yao, Xianglong Liang, Shuping Wang, Jianyong Yao
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Coupling effect of machine tool dynamic characteristics and cutting conditions on the cutting process vibration and high-speed micro-planing surface mid-frequency waviness Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-06 Lizi Qi, Min Zhu, Qiang Gao, Yabo Zhang, Guoyu Fu, Qi Cui, Siyu Gao, Wenyuan Wei, Lexiang Wang, Lihua Lu
In addition to the dynamic characteristics of the machine tool, cutting conditions significantly influences the vibration of the cutting system and mid-frequency waviness of the workpiece surface in ultra-precision machining (UPM). In this work, the effects of cutting conditions on machining vibration and surface waviness were investigated by high-speed micro-planning experiments. The origin of vibration
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Basis pursuit set selection for nonlinear underconstrained problems: An application to damage characterization Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-06 Dionisio Bernal, Martin D. Ulriksen
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An experimental approach to multi-input multi-output nonlinear active vibration control of a clamped sandwich beam Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-06 Celia Hameury, Giovanni Ferrari, Giulio Franchini, Marco Amabili
Large amplitude vibrations are often associated with geometric nonlinearity. These nonlinear systems are usually controlled using linear controllers, such as positive position feedback (PPF). Nonlinear control has also often been limited to single-input single-output (SISO) architectures. The present study develops a nonlinear PPF controller implemented with both a SISO and a multiple-input multiple-output
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Iterative improvement in tacholess speed estimation using instantaneous error estimation for machine condition monitoring in variable speed Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-06 Dikang Peng, Wade A. Smith, Robert B. Randall, Ke Feng, Zhongxiao Peng, Wei Teng, Yibing Liu
Knowing the instantaneous angular speed (IAS) is crucial for monitoring the condition of variable speed rotating machinery. Thanks to advantages such as cost-saving, simplicity, and reduced installation difficulties, tacholess speed estimation (TSE) methods, based on the vibration signal itself, have attracted increasing attention in recent years. The major problem limiting the use of TSE methods in
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Spring-like behavior of cementitious composite enabled by auxetic hyperelastic frame Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-05-06 Yading Xu, Zhaozheng Meng, Rowin J.M. Bol, Branko Šavija
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Leveraging digital twin into dynamic production scheduling: A review Robot. Comput.-Integr. Manuf. (IF 10.4) Pub Date : 2024-05-04 Nada Ouahabi, Ahmed Chebak, Oulaid Kamach, Oussama Laayati, Mourad Zegrari
The digital twin is an emerging technology that enhances industrial digitalization, as it establishes a dynamic virtual model that emulates a specific phenomenon of the corresponding physical system, thus imparting added value in many manufacturing activities. Production scheduling is one of the manufacturing activities that can fulfill step-improvements from the digital twin. However, modest endeavors
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M-band wavelet network for machine anomaly detection from a frequency perspective Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-04 Zuogang Shang, Zhibin Zhao, Ruqiang Yan, Xuefeng Chen
The autoencoder (AE) is widely utilized in deep anomaly detection, but it lacks explainability due to the complexity of nonlinear mapping. One approach to address this issue is incorporating wavelet theory, which shares similarities in decomposition and reconstruction procedures. However, the perfect reconstruction property of wavelet theory conflicts with AE-based anomaly detection. To tackle this
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Robustness analysis and experimental validation of a deep neural network for acoustic source imaging Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-04 Qing Li, Elias J.G. Arcondoulis, Sheng Wei, Pengwei Xu, Yu Liu
Deep Neural Network (DNN) models offer an attractive alternative to existing acoustic source imaging techniques, such as acoustic beamforming, due to their ever-growing potential with increasing computational power. Source resolution of acoustic beamforming methods is limited at lower frequencies and their source maps may possess sidelobes at higher frequencies. However, acoustic beamforming methods
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Weight extracting transform for instantaneous frequency estimation and signal reconstruction Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-04 Cuiwentong Xu, Yuhe Liao
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A Gaussian-process assisted model-form error estimation in multiple-degrees-of-freedom systems Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-04 Sahil Kashyap, Timothy J. Rogers, Rajdip Nayek
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A patterned vibrotactile method using envelope modulation with high resolution and low perceptual frequency Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-04 Hangyu Li, Zewei Hou, Jijing Huang, Li Zhou, Yongmao Pei
The virtual haptics is a crucial aspect of immersive virtual reality, extending the traditional experiences of sight and hearing. The vibration can provide direct normal vibration and friction reduction, making it a promising method to realize virtual haptics. However, the optimum perceptual threshold of skin for vibration is 100 Hz to 500 Hz, resulting in a too low vibrotactile resolution. The conflict
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Impact behavior of periodic, stochastic, and anisotropic minimal surface-lattice sandwich structures Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-05-04 Chukwugozie J. Ejeh, Imad Barsoum, Rashid K. Abu Al-Rub
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Composite continuum robots: Accurate modeling and model reduction Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-05-04 Gang Zhang, Jing Su, Fuxin Du, Xingyao Zhang, Yibin Li, Rui Song
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Machine vision and novel attention mechanism TCN for enhanced prediction of future deposition height in directed energy deposition Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-03 Miao Yu, Lida Zhu, Jinsheng Ning, Zhichao Yang, Zongze Jiang, Lu Xu, Yiqi Wang, Guiru Meng, Yiming Huang
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Feedback control system for vibration construction of fresh concrete Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-03 Jiajie Li, Zhenghong Tian, Yuanshan Ma, Lujia Li, Weihao Shen, Jiaxing Zhao
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Constructing nonlinear data-driven models from pitching wing experiments using multisine excitation signals Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-03 M.F. Siddiqui, P.Z. Csurcsia, T. De Troyer, M.C. Runacres
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A mechanics-informed neural network method for structural modal identification Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-03 Yuequan Bao, Dawei Liu, Hui Li
Modal identification is one of the core topics within the realm of structural health monitoring (SHM). In this study, we summarize four modal mechanical properties and propose a mechanics-informed neural network (MINN) method for structural modal identification. The proposed MINN method incorporates the sparsity of the data in the time–frequency domain and cross-correlation minimization in the time
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Smooth least absolute deviation estimators for outlier-proof identification Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-03 Janusz Kozłowski, Zdzisław Kowalczuk
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Cavitation morphology and erosion on hydrofoil with slits Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-05-03 Ning Qiu, Pei Xu, Han Zhu, Wenjie Zhou, Doubin Xun, Minwei Li, Bangxiang Che
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High temperature and mesostructure effect on aluminum foam compression responses Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-05-03 Sihang Xiao, Zeang Zhao, Shengyu Duan, Yanfei Chen, Yaoqi Wang, Panding Wang, Hongshuai Lei
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Dynamic modeling and analysis considering friction-wear coupling of gear system Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-05-03 Kairan Zhang, Rulin Shen, Zehua Hu, Jinyuan Tang, Zhou Sun, Aodong Ning, Shuhan Yang
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GPNet: A Deep Learning Guided Projectiles Navigation Framework IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-05-03 Jinwen Wang, Zhihong Deng, Kai Shen, Yuming Bo
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Theoretical and experimental study of a stable state adjustable nonlinear energy sink Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-02 You-Cheng Zeng, Hu Ding, Jin-Chen Ji, Li-Qun Chen
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An improved LuGre friction model and its parameter identification of structural interface in thermal environment Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-02 Tichang Jia, Jie Liu, Yunzhao Wang, Chaofeng Li, Haoyan Zhang
In this paper, an improved LuGre model was established based on the micro-convex assumption, Hertz contact theory, and thermal conditions. The displacement-tangential force and velocity-tangential force hysteresis curves under different temperature conditions were obtained by the dry friction testing experiment. Further, this paper constructed an objective function for the proposed friction model,
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Stability prediction method of time-varying real-time hybrid testing system on vehicle-bridge coupled system Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-02 Hao Liu, Zhenyun Tang, Ryuta Enokida
In recent years, real-time hybrid testing (RTHT) has been applied for the dynamic testing of high-speed trains running on bridges. A guarantee of stability for the RTHT system is essential to achieve a safe and reliable result. However, the inherent time-varying characteristics of the vehicle-bridge coupled system pose challenges to RTHT stability prediction. This study aims to develop a stability
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A novel mirror-assisted method for full-field vibration measurement of a hollow cylinder using a three-dimensional continuously scanning laser Doppler vibrometer system Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-02 K. Yuan, W.D. Zhu
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Design and Control of a Novel Active Shoulder Exoskeleton for Overhead Work Assistance IEEE ASME Trans. Mechatron. (IF 6.4) Pub Date : 2024-05-02 Shuo Ding, Ashwin Narayan, Francisco Anaya Reyes, Shuishuai Han, Haoyong Yu
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Learning-based adaption of robotic friction models Robot. Comput.-Integr. Manuf. (IF 10.4) Pub Date : 2024-05-01 Philipp Scholl, Maged Iskandar, Sebastian Wolf, Jinoh Lee, Aras Bacho, Alexander Dietrich, Alin Albu-Schäffer, Gitta Kutyniok
In the Fourth Industrial Revolution, wherein artificial intelligence and the automation of machines occupy a central role, the deployment of robots is indispensable. However, the manufacturing process using robots, especially in collaboration with humans, is highly intricate. In particular, modeling the friction torque in robotic joints is a longstanding problem due to the lack of a good mathematical
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Zero group velocity feature in CFRP-Nomex honeycomb structure and its use for debonding detection Mech. Syst. Signal Process. (IF 8.4) Pub Date : 2024-05-01 Ye Yuan, Bin Liu, Zhengxiao Sha, Zhiguo Zhang, Zheng Wang
Carbon fiber reinforced plastic (CFRP) − Nomex adhesive honeycomb structures are widely used in aerospace due to their excellent properties. However, debonding defects pose a significant challenge to structural safety due to their hidden nature and high risk. In this work, to address the debonding detection in the CFRP-Nomex honeycomb structure, a method based on the zero group velocity (ZGV) feature
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Measurement of the local static mechanical pressure of earplugs Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-05-01 Luiz G.C. Melo, Ahmed S. Dalaq, Franck Sgard, Olivier Doutres, Laurianne Legroux, Eric Wagnac
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Bionic functional membranes for separation of oil-in-water emulsions Friction (IF 6.8) Pub Date : 2024-05-01 Chaolang Chen, Ruisong Jiang, Zhiguang Guo
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Core-rim structured MXene@SiO2 composites as oil-based additives for enhanced tribological properties Friction (IF 6.8) Pub Date : 2024-05-01 Yuhong Cui, Shenghua Xue, Tiantian Wang, Shujuan Liu, Qian Ye, Feng Zhou, Weimin Liu
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Privacy-preserving federated transfer learning for defect identification from highly imbalanced image data in additive manufacturing Robot. Comput.-Integr. Manuf. (IF 10.4) Pub Date : 2024-04-30 Jiafeng Tang, Zhibin Zhao, Yanjie Guo, Chenxi Wang, Xingwu Zhang, Ruqiang Yan, Xuefeng Chen
Defect identification is a crucial task for process monitoring and quality evaluation in additive manufacturing (AM). Deep learning (DL) has shown great potential for diverse fields, but some challenges have hindered the application in AM process monitoring. Firstly, DL-based methods are driven by big data and require a large number of training data. However, in reality, defective data is often rare
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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 novel model-based welding trajectory planning method for identical structural workpieces Robot. Comput.-Integr. Manuf. (IF 10.4) Pub Date : 2024-04-29 Weihua Fang, Xincheng Tian
Welding robots have been widely used with the development of manufacturing industry. At present, welding trajectory planning and programming of welding robots are performed separately for similar (structural) workpieces with different dimensions or deformations. Besides, the welding torch pose planning using conventional robot programming methods is time-consuming for workpieces with complex welding
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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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Size effects and the existence of scalable materials and systems Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-04-29 Keith Davey, Wenyue Gai, Hamed Sadeghi, Rooholamin Darvizeh
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Effect of spatial setting angle on vibration of elastically restrained rotating beams Int. J. Mech. Sci. (IF 7.3) Pub Date : 2024-04-29 Zhu Su, Lifeng Wang, Xiaohu Ma
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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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A novel collision detection method based on current residuals for robots without joint torque sensors: A case study on UR10 robot Robot. Comput.-Integr. Manuf. (IF 10.4) Pub Date : 2024-04-27 Tian Xu, Hua Tuo, Qianqian Fang, Debin Shan, Hongzhe Jin, Jizhuang Fan, Yanhe Zhu, Jie Zhao
Existing model-based collision detection methods rely on accurate torque dynamic parameters identified using measured joint torques. However, for robots lacking joint torque sensors, only joint currents can be measured, and joint torques must be estimated through the linear relationship between joint currents and joint torque constants. This way can lead to cumulative identification errors in torque
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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