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Novel mining conveyor monitoring system based on quasi-distributed optical fiber accelerometer array and self-supervised learning Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-12 Hua Zheng, Huan Wu, Hao Yin, Yuyao Wang, Xinliang Shen, Zheng Fang, Dingjiong Ma, Yun Miao, Li Zhou, Min Yan, Jie Sun, Xiaoli Ding, Changyuan Yu, Chao Lu
Belt conveyors in mining are crucial, with downtime leading to significant losses and safety hazards. Unplanned shutdowns often result from idler failures. To address this, an online monitoring system for continuous idler health assessment is proposed. Considering the large number and dense spatial distribution of idlers over long distances, this work presents a system that utilizes a quasi-distributed
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An adaptive convolutional neural network based on transmissibility grayscale image for online identification of offshore platform damage pattern Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-11 Jiancheng Leng, Jinyong Ma, Huiyu Feng
In response to the challenges in offshore platform damage pattern recognition, where traditional methods lack adaptability owing to relying on feature extraction and expert knowledge, a novel method for online recognition of offshore platform damage patterns using an improved convolutional neural network (CNN) based on transmissibility grayscale image is proposed. The original transmissibility function
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A signal energy-based approach for acoustic source localization in composite laminates Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-10 Chenning Ma, Zixian Zhou, Jinxia Liu, Zhiwen Cui, Tribikram Kundu
Composite laminates are widely used in various fields, but their structural properties make them prone to impact damage. Thus, the real-time localization of the impact source in composite laminates is of great importance. The signal energy-based approach for acoustic source localization, as a new technique proposed in recent years, has advantages in that it can be applied in the case of low signal-to-noise
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Theoretical modeling and performance analysis on the linear electromagnetic actuator with high nonlinear dynamic negative stiffness Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-10 Chuchao Wang, Shizhou Lu, Xiaohan Liu, Wenyin Mo, Bin Zhang, Kai Li, Lining Sun
In order to improve the dynamic performance and load resistance of linear electromagnetic actuators, a novel linear solenoid elastic actuator with higher nonlinear negative stiffness and speed is proposed. In this paper, the nonlinear force–displacement relationship and transient performance of the actuator is analyzed and predicted. The analytical, numerical and finite element methods are used to
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A data-driven approach for rapid detection of aeroelastic modes from flutter flight test based on limited sensor measurements Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-09 Arpan Das, Pier Marzocca, Giuliano Coppotelli, Oleg Levinski, Paul Taylor
Flutter flight test involves the evaluation of the airframe’s aeroelastic stability by applying artificial excitation on the aircraft lifting surfaces. The subsequent responses are captured and analyzed to extract the frequencies and damping characteristics of the system. However, noise contamination, turbulence, non-optimal excitation of modes, and sensor malfunction in one or more sensors make it
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Element-wise parallel deep learning for structural distributed damage diagnosis by leveraging physical properties of long-gauge static strain transmissibility under moving loads Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-09 Yu-Song Liu, Wang-Ji Yan, Ka-Veng Yuen, Wan-Huan Zhou
The Transmissibility Function (TF) has gained considerable interest in structural damage detection because of its relatively high sensitivity to damage and robustness to excitation. This study proposed a distributed damage diagnosis method for beam-like structures based on a long-gauge static strain TF defined as the ratio of the Fourier transform of static strain response under moving loads from a
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Frequency shaping-based H∞ control for active pneumatic vibration isolation with input voltage saturation Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-08 Shaofeng Xu, Xiaoxia Liu, Yixuan Wang, Zhibo Sun, Jifan Wu, Yan Shi
Pneumatic vibration isolators play an increasingly important role in precision manufacturing. In this paper, a H∞ active control strategy for pneumatic vibration isolation system based on voltage input saturation is proposed and studied. The objective is to suppress the resonance peaks and low-frequency vibration disturbances near the intrinsic frequency of the vibration isolation system. The control
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A pendulum-type annular dielectric elastomer generator for multi-directional ultra-low-frequency vibration energy harvesting Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-08 Zhihui Lai, Mengyao Wu, Jianwei Zhang, Zhouzhou Wang, Aijie Feng, Bangjie Lin, Runye Shi, Bin Xu, Daniil Yurchenko, Shitong Fang
Currently, dielectric elastomer generators (DEGs) demonstrate high energy density, rapid response, and simple structure in the field of energy harvesting (EH). However, the efficient multi-directional dielectric EH in complex vibrational environments, particularly at ultra-low frequencies (0–3 Hz), remains a significant challenge. To solve this issue, a pendulum-type annular DEG (PA-DEG) is designed
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Intelligent framework for unsupervised damage detection in bridges using deep convolutional autoencoder with wavelet transmissibility pattern spectra Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-08 Shuai Li, Yuxi Cao, Emmanuel E. Gdoutos, Mei Tao, Nizar Faisal Alkayem, Onur Avci, Maosen Cao
Deep Learning has been increasingly utilized in structural damage detection. Existing relevant studies often highlight the benefits of supervised deep learning in the intelligent identification of bridge damage. Notably, however, supervised deep learning methods encounter specific challenges in processing real-world monitoring data to reflect damage. Typical challenges include: (i) the need for a large
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Improved energy harvesting by enhanced nonlinearities: New phenomena and experimental demonstration Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-06 Yongheng Yu, Fengming Li
This paper investigates a nonlinear piezoelectric energy harvesting system that enhances conversion of mechanical energy to electrical energy by integrating piezoelectric materials with a nonlinear system. The research simplifies a flexible beam with macro fiber composite (MFC) piezoelectric patches using a lumped-parameter approach and derives the dynamic equations of the system using the Lagrange
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Adaptive linear chirplet synchroextracting transform for time-frequency feature extraction of non-stationary signals Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-06 Zhu Yan, Jingpin Jiao, Yonggang Xu
Time-frequency analysis methods is an effective tool to analyze non-stationary signals. Moreover, the utilization of postprocessing algorithms significantly enhances this analytical capability. However, these methods have certain limitations when dealing with non-stationary signals with strong time-varying laws. We put forward an adaptive linear chirplet synchroextracting transform (ALCSET) based on
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Ultrasonic reflection measured oil film thickness in the slipper bearings of an aviation fuel piston pump Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-06 Peng Zheng, Pan Dou, Quanzhong Wu, Yaping Jia, Tonghai Wu, Min Yu, Yaguo Lei, Tom Reddyhoff
Running on an ultra-thin dynamic oil film, the slipper bearing in an aviation fuel piston pump is vulnerable to lubrication failure. To improve lubrication performance, the slipper surface is often grooved. However, the eventual lubrication effects remain challenging to judge qualitatively due to inaccessible measurement of oil film thickness distribution during pump operation. Eddy current sensors
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The flexible tensor singular value decomposition and its applications in multisensor signal fusion processing Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-06 Jinfeng Huang, Feibin Zhang, Babak Safaei, Zhaoye Qin, Fulei Chu
A tensor, represented as a multidimensional array, has crucial applications in various fields such as image processing and high-dimensional data mining. This study defines a novel concept of tensor-tensor multiplication, the ‘-order 〈, 〉-mode product’, laying a foundational framework for advanced tensor operations. Building on this, a novel extension of matrix SVD to tensors, termed the flexible tensor
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A novel tuned liquid mass damper for low-frequency vertical vibration control: Model experiments and field tests Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-05 Zhengxing Wang, Xiaopeng Chai, Sijie Peng, Bo Wang, Lianzhen Zhang
To address the issue of excessive static stretching in tuned mass damper (TMD) used for vertical vibration control of low-frequency structures, a novel tuned liquid mass damper (TLMD) is proposed in the present study, and corresponding theoretical analysis and experimental investigation are carried out. The proposed TLMD consists of a mass-spring oscillator and a tank filled with liquid, with the mass
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Near-field acoustic emission source localization method based on orthogonal matching pursuit under nonuniform linear array Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-05 Xin Fang, Guijie Liu, Honghui Wang, Weilei Mu, Yingchun Xie, Xiaojie Tian, Dingxin Leng, Gongbo Li, Guanghao Li
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Thermo-acoustoelastic modeling of guided wave propagation in plate/shell structures under temperature-stress coupling Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-05 Xu Zhang, Lei Chen, Wei Du, Gang Liu, Zehui Zhang
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Rotor dynamic behaviors of a novel bearing system with bi-directional tilting effects: Experiment and theory Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-05 Zhongliang Xie, Kang Yang, Wenjun Gao, Bin Zhao, Peng Du, Meng Zhang
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Inversing spatial modulus distribution of CFRTP by a nondestructive vibrational method Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-04 Weizhao Huang, Ye Zhang, Yi Wan, Jun Takahashi
To obtain a detailed distribution of modulus for fine finite element (FE) simulation of carbon fiber-reinforced thermoplastic, a non-destructive vibrational method is proposed by considering the tested natural frequencies as iteration targets and using genetic algorithm to update the modulus in the FE model. Mass blocks are attached using various distributions to create supplemental constraints. Two
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A lognormal-normal mixture model for unsupervised health indicator construction and its application into gear remaining useful life prediction Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-04 Dingliang Chen, Fei Wu, Yi Wang, Yi Qin
Accurately predicting the remaining useful life (RUL) of a key component, such as gear, is significant for guaranteeing the safe operation of mechanical equipment and making a proper maintenance plan. The health indicator (HI) plays an essential role in the data-driven RUL prediction technique. HI can be constructed from the perspective of the data distribution discrepancy. However, some existing methods
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A novel modelling method for heavy-haul train-track-long-span bridge interaction considering an improved track-bridge relationship Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-04 Qinglie He, Shihui Li, Yun Yang, Shengyang Zhu, Kaiyun Wang, Wanming Zhai
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Bolted lap joint loosening monitoring and damage identification based on acoustic emission and machine learning Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-04 Xiao Wang, Qingrui Yue, Xiaogang Liu
Monitoring bolt looseness in joint structures is vital for their safety and integrity. The relationship between bolt looseness-sensitive acoustic emission (AE) feature selection and damage mechanisms is unclear. This research combines AE monitoring with machine learning to identify bolt looseness levels and wear mechanisms. Using gradient-boosting tree-based ensemble machine learning models, we evaluated
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Dynamic modeling and oscillation control of industrial cranes transporting upright slender flexible payloads Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-04 Chenglei Yang, Jie Huang, William Singhose
Industrial cranes transporting slender payloads in an upright position have been used in several applications. However, the swing of the cable-suspended object may interact with the bending vibrations of the slender payload during motions. The interaction-induced vibrations exhibit complicated dynamical behavior and corrupt the safety and efficiency of the material movement. While significant work
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On the existence of mode-coupling chatter in robotic milling based on chatter type indicators extracted by dynamic mode decomposition Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-04 Si-Hao Mao, Song-Tao Ye, Yan-Ru Jiang, Chang-Qing Shen, Xiao-Jian Zhang, Si-Jie Yan, Han Ding
In the stability analysis of robotic milling processes, two primary chatter mechanisms have been identified — regenerative chatter and mode-coupling chatter. They are known to result in undesirable outcomes such as poor surface finish, dimensional errors, and reduced lifespan of tools and machines. Recently, there is increasing disagreement regarding the existence of mode-coupling chatter. Specifically
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A two-degree-of-freedom nonlinear electromagnetic energy harvester in rotational motion Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-03 Shuzhe Zhou, Zhiyuan Li, Shengxi Zhou
Electromagnetic energy harvesting has sparked the interest of researchers due to its promising potential in powering miniaturized electronic systems and wireless sensor networks. This paper focuses on a two-degree-of-freedom nonlinear electromagnetic energy harvester (2DOF-NEMEH) using a magnetic levitation architecture in rotational motion. The residual magnetic flux density is identified by the finite
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Theoretical and experimental investigations on large-deformation dynamics of the standing cantilevered pipe conveying fluid Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-03 Wei Chen, Hao Yan, Runqing Cao, Huliang Dai, Lin Wang
Flexible pipes conveying fluid commonly exist in practical engineering. Its rich dynamic behaviors have attracted remarkable attention from researchers. The standing cantilevered pipe conveying fluid with the significant gravity effect is supposed to exhibit interesting dynamic behaviors. However, since the geometric nonlinearity was approached by the Taylor expansion in the traditional theoretical
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Modelling metro-induced environmental vibration by combining physical-numerical and deep learning methods Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-03 Jiaru Wang, Xinbiao Xiao, Laixian Peng, Jianuo Wang, Yuanpeng He, Xiaozhen Sheng
With the development of urban rail transit, environmental vibration caused by trains has garnered increasing attention. In the research on environmental vibration induced by trains, commonly employed methods include physics-based models grounded in mathematical principles, transfer function approaches and deep learning methods based on experimental data. Among these methods, physics-based models based
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Multi-output multi-physics-informed neural network for learning dimension-reduced probability density evolution equation with unknown spatio-temporal-dependent coefficients Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-03 Teng-Teng Hao, Wang-Ji Yan, Jian-Bing Chen, Ting-Ting Sun, Ka-Veng Yuen
The Dimension-Reduced Probability Density Evolution Equation (DR-PDEE) offers a promising approach for evaluating probability density evolution in stochastic dynamical systems. Physics-Informed Neural Networks (PINNs) are well-suited for solving DR-PDEE due to their ability to encode physical laws into the learning process. However, challenges arise from the spatio-temporal-dependence of unknown intrinsic
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A multi-objective trajectory planning approach for vibration suppression of a series–parallel hybrid flexible welding manipulator Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-03 Caixia Ban, Bing Fu, Wei Wei, Zhaotao Chen, Shengnan Guo, Nianchun Deng, Lili Yuan, Yu Long
Although the series–parallel hybrid welding manipulator has advantages over the traditional series manipulator, its must run continuously and smoothly according to a specific trajectory at the rated velocity. Considering a flexible manipulator with a complex series–parallel hybrid structure as the research object, this paper proposes a multi-objective approach to indirectly suppress the vibration.
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Investigation of time-varying frequencies of two-axle vehicles and bridges during interaction using drive-by methods and improved multisynchrosqueezing transform Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-03 Zhenkun Li, Yifu Lan, Kun Feng, Weiwei Lin
Recent studies have highlighted the superiority of the drive-by method using vehicle responses to identify bridge frequencies due to its cost-effectiveness. However, most research identifies bridge and vehicle frequencies as time-invariant, which neglects the non-stationary nature of vehicle–bridge interaction systems. This assumption holds true only when the vehicle’s mass is significantly less than
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Numerical analysis and experimental validation of the coupled thermal effects in swashplate type axial piston machines Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-03 Swarnava Mukherjee, Lizhi Shang, Andrea Vacca
This paper explores the significant impact of thermal effects on the performance of Swashplate-Type Axial Piston Machines, a crucial aspect often overlooked in current numerical analyses primarily focused on energy efficiency prediction and machine design optimization. Existing methods commonly neglect or only partially account for thermal dynamics and heat transfer within both fluid and solid domains
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Nonlinear Lamb wave phased array for revealing micro-damage based on the second harmonic reconstruction Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-02 Haiming Xu, Lishuai Liu, Xuan Li, Siyuan Peng, Yanxun Xiang, Fu-Zhen Xuan
It is challenging but meaningful to detect and image the micro-damage in the early stages of engineering structure failure. The nonlinear ultrasonic technique has gained considerable attention for micro-damage detection, meanwhile, the Lamb wave phased array technique has become a practical tool for macro-damage imaging. The combination of these two techniques can pave a promising way for micro-damage
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A purely centered and non-redundant piezoelectric stick-slip rotary stage with force amplification Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-02 Shi-kun Ma, Yi-ling Yang, Yu-guo Cui, Gao-hua Wu, Yan-ding Wei
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Adaptive residual spectral amplitude modulation: A new approach for bearing diagnosis under complex interference environments Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-02 Sen Li, Ming Zhao, Yiyang Wei, Shudong Ou, Dexin Chen, Linjiao Wu
Rolling bearings are a vital component for transmitting and supporting in rotating machinery. They are susceptible to failure since their operation under high speeds and heavy loads. Bearing failure may disrupt the manufacturing process and cause catastrophic accidents. Therefore, condition monitoring for bearings is essential to minimize operational disruptions and avoid unforeseen casualties. High-frequency
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Heterogeneous graph representation-driven multiplex aggregation graph neural network for remaining useful life prediction of bearings Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-02 Yongchang Xiao, Dongdong Liu, Lingli Cui, Huaqing Wang
Graph neural networks (GNNs) can capture interdependencies between data with the structured data modeling ability, and have received much attention from industry professionals in remaining useful life (RUL) prediction tasks. However, the existing methods assume that graph nodes and edges are of the same homogeneous attributes, which leads to information loss and cannot fully capture the complex degeneration
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Convolutional autoencoders and CGANs for unsupervised structural damage localization Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-02 Rafael Junges, Zahra Rastin, Luca Lomazzi, Marco Giglio, Francesco Cadini
The present work introduces two unsupervised data-driven methodologies for processing Lamb waves (LWs) to localize structural damage, specifically employing convolutional autoencoders (CAEs) and conditional generative adversarial networks (CGANs). Both techniques are capable of processing diagnostic signals without the need for any prior feature extraction. Once all signals are processed, a damage
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Acoustic inversion method based on the shear flow Green’s function for sound source localization in open-jet wind tunnels Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-01 Daofang Feng, Liang Yu, Long Wei, Youtai Shi, Wei Pan, Min Li
While localizing sound sources within the shear flow, conventional beamforming faces limitations due to the Rayleigh criterion, restricting its resolution. Moreover, acoustic inversion method encounters challenges in establishing the relationship between source strength and acoustic quantities within the shear flow, considering the effects of convection, refraction, and reflection. This paper introduces
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A novel method for remaining useful life of solid-state lithium-ion battery based on improved CNN and health indicators derivation Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-07-01 Yan Ma, Zhenxi Wang, Jinwu Gao, Hong Chen
The remaining useful life (RUL) of solid-state lithium-ion battery (SSLIB) is a crucial challenge for their future marketability due to the fact that it guarantees the safety and reliability for electric vehicles (EV) under complex degradation mechanisms. To address this issue, a novel RUL prediction approach based on improved convolutional neural network (CNN) and derived health indicators (HIs) from
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Welded joints stiffness and damping characterisation based on model updating and texture analysis Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-29 Kshitij Shrivastava, Kiran Vijayan, Saumya Gupta, Arjun Mahato, Shibayan Roy, Vikas Arora
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Robust and fast backbone tracking via phase-locked loops Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-29 Patrick Hippold, Maren Scheel, Ludovic Renson, Malte Krack
Phase-locked loops are commonly used for shaker-based backbone tracking of nonlinear structures. The state of the art is to tune the control parameters by trial and error. In the present work, an approach is proposed to make backbone tracking much more robust and faster. A simple PI controller is proposed, and closed-form expressions for the gains are provided that lead to an optimal settling of the
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Vibration transmission through a cantilever beam in mass impacting metamaterial: An analytical investigation and experimentation Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-29 Muskaan Sethi, Arnab Banerjee, Bappaditya Manna
This paper presents a novel form of mass-in-mass metamaterial, in which the internal resonator is replaced by a beam. Additionally, stoppers are installed on either side of the beam connected rigidly with the main mass to produce an impacting response. Employing linear complementary problem (LCP) along with Euler’s discretization, a time domain solver is developed to obtain the response of the impacting
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An optimal sensor layout method based on noise reduction estimation for active road noise control Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-29 Can Cheng, Zhien Liu, Xiaolong Li, Chihua Lu, Wan Chen
Active noise control (ANC) is an effective method to suppress vehicle road noise. The rapid selection of the reference sensor set and rational selection of its layout position are crucial for determining the vibration noise transmission paths with high contributions, which determines the noise reduction performance of the active road noise control (ARNC) system. The reference sensor set selected by
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Research on the performance of GMCBO methodology based on model updating of a pedestrian bridge Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-28 Zhiyuan Xia, Huiyuan Shi, Baijian Tang, You Wang, Xin Chen, Sheng Gu
Consider the loss of diversity of the bodies at the later optimization stage and the low efficiency of the global searching ability of the traditional colliding bodies optimization algorithm in dealing with complex optimization issues of practical structures. Herein, an improved colliding bodies optimization method combing Gaussian-white-noise mutation and innovative collision mode is proposed. The
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Ultrasonic dynamic plane wave imaging for high-speed railway inspection Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-28 Zhixuan Chang, Xintao Xu, Shiwei Wu, Eryong Wu, Keji Yang, Jian Chen, Haoran Jin
The detection of internal defects within railway tracks stands as a critical aspect of ensuring transport security, given its potential to precipitate severe accidents. Phased array ultrasonic testing methods have gained extensive usage in rail inspection owing to their remarkable precision and expansive coverage. Traditional ultrasonic inspection techniques typically require either a fixed relative
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Localization and quantification of delamination/disbond inside a composite lap-joint using novel cross and drive point mechanical impedance based feature Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-28 Umakanta Meher, Mohammed Rabius Sunny
This work proposes an electro mechanical impedance based approach for detection of disbonds in a composite lap joint using both drive point and cross mechanical impedance signature. An approximate analytical model has been developed for determination of drive point and cross mechanical impedance of a composite lap joint for given location and size of disbond. Electro-mechanical impedance response of
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Modification of the transfer matrix method for the sonic black hole and broadening effective absorption band Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-28 Yunwei Chen, Kangfan Yu, Qidi Fu, Jianrun Zhang, Xi Lu
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Coherence-based phase aberration correction and beamforming for ring-array ultrasound imaging Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-28 Zhengfeng Lan, Chao Rong, Changshan Han, Xiaolei Qu, Jingsong Li, Hongxiang Lin
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Vibration shock disturbance modeling in the rotating machinery fault diagnosis: A generalized mixture Gaussian model Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-28 Ran Wang, Zhixin Gu, Chaoge Wang, Mingjie Yu, Wentao Han, Liang Yu
In real-world industrial environments, complex background noises are composed of various components, deviating from a simple Gaussian distribution like shock noise. In this work, a robust noise modeling method based on the mixture of exponential power (MoEP) distributions is developed to address this issue. To proficiently extract the fault characteristics, the signal’s 2-D representation is attained
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Nonstationary random vibration analysis of hysteretic systems with fractional derivatives by FFT-based frequency domain method Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-27 Ning Zhao, Xu Wang, Yu Wu
Nonstationary random vibration problems of nonlinear fractional systems are challenging and drawing increasing attention. This study presents an efficient numerical method for the random vibration analysis of large-scale nonlinear fractional systems subjected to fully nonstationary excitations. Firstly, the fast Fourier transform (FFT)-based frequency domain method originally proposed for the nonstationary
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Spatiotemporal energy regulation strategy for enhancing SNR and spatial resolution in the damage detection with SH0 waves Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-27 Qiangxin Li, Jian Feng, Qi Xiao, Yunning Feng
The fundamental shear horizontal (SH0) wave, which can be generated by electromagnetic acoustic transducers (EMATs), is widely used in the structural health monitoring fields owing to its non-dispersive nature and the ability to detect over long distances. However, current SH0 wave methods hardly achieve the excellent signal-to-noise ratio (SNR) of the echo signals and satisfactory spatial resolution
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Rotating machinery weak fault features enhancement via line-defect phononic crystal sensing Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-27 Jiawei Xiao, Xiaoxi Ding, Wenbin Huang, Qingbo He, Yimin Shao
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Automatic damping estimation via bootstrap technique and Bayesian analysis for mechanical system condition monitoring Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-27 Stipe Perišić, Jani Barle, Ivan Tomac, Predrag Đukić
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StocIPNet: A novel probabilistic interpretable network with affine-embedded reparameterization layer for high-dimensional stochastic inverse problems Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-27 Jiang Mo, Wang-Ji Yan
The stochastic inverse problem (StocIP), which aims to align push-forward and observed output distributions by estimating probability distributions of unknown system inputs, often faces optimization challenges and the curse of dimensionality. A novel deep network called StocIPNet which comprises an affine-embedded reparameterization subnetwork (ReparNet) and a complex system metamodeling subnetwork
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Experimental characterization of bending modes and investigation of multi-stable solutions of PLA-based additively manufactured beams Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-26 M. Trujillo, M. Cheng-Guajardo, M. Curtin, A. Abdelkefi
This study examines the experimental characterization of three identically 3D printed polylactic acid (PLA)-based cantilever beams subjected to various vibrational excitations with investigating the possible existence of multiple solutions and compares the results of the beams to one another to reveal uncertainties and possible issues of reproducibility of the additively-manufactured systems. Free
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Harnessing guided waves for long-range monitoring of damaged rails Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-26 Emanuele Riva, Gabriele Cazzulani, Marcella Di Mario, Fabio Senesi, Luca Ricciardi, Francesco Braghin
We experimentally unveil the monitoring capabilities of guided waves in the context of railways engineering when operating in a harsh environment. To this end, the integrity of damaged rails is probed by way of resonant and nonresonant transduction mechanisms based on piezoelectric sensing and actuation. The experimental analysis is accomplished through the selective excitation and measurement of guided
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Damage identification in sandwich structures using Convolutional Neural Networks Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-26 Ian Dias Viotti, Ronny Francis Ribeiro Jr., Guilherme Ferreira Gomes
The increasing complexity of structures and materials, coupled with ever more stringent demands for safety and cost reduction in maintenance operations, has driven the need to develop advanced techniques for structural integrity monitoring, known as Structural Health Monitoring (SHM). In this context, this study investigates the use of image processing techniques of mode shapes in a composite sandwich
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Differential capacitive mass sensing based on mode localization in coupled microbeam arrays Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-26 Fehmi Najar, Mehdi Ghommem, Toky Rabenimanana, Mohamed Hemid, Vincent Walter, Najib Kacem
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Identification for nonlinear systems modelled by deep long short-term memory networks based Wiener model Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-26 Feng Li, Yuesong Yang, Yuanqing Xia
This paper is concerned with modeling and identification methodology for practical nonlinear system via deep long short-term memory (DLSTM) networks-based Wiener model. To determine the unknown parameters and simplify parameters identification procedure for the Wiener model, a two-step identification scheme is implemented applying hybrid signals involving separable signal and random data. First, the
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Motion magnification for video-based vibration measurement of civil structures: A review Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-25 Kui Luo, Xuan Kong, Jinzhao Li, Jiexuan Hu, Lu Deng
Vibration measurement plays an important role in the inspection and monitoring of civil structures. In recent years, the computer vision (CV)-based method has gained significant popularity in the field of vibration measurement for civil structures due to its inherent advantages, such as non-contact, low cost, long-distance measurement, and ease of implementation. However, those traditional CV-based
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Physics-informed neural network for velocity prediction in electromagnetic launching manufacturing Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-25 Hao Sun, Yuxuan Liao, Hao Jiang, Guangyao Li, Junjia Cui
Electromagnetic launching manufacturing (EMLM) is a high-speed material processing technique powered by pulsed current. The hammer velocity is a key indicator in EMLM, but it is hard to obtain. A viable approach is to use the circuit response current to help in measuring the hammer velocity, but the different curve patterns and the weak interactions between the parameters are major hindrances. In this
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Data-driven modeling of multi-stable origami structures: Extracting the global governing equation and exploring the complex dynamics Mech. Syst. Signal Process. (IF 7.9) Pub Date : 2024-06-25 Zuolin Liu, Xiaoxu Zhang, Kon-Well Wang, Jian Xu, Hongbin Fang
In recent years, multi-stable origami structures have garnered increasing attention for their applications in dynamic scenarios such as robotic arm motions, impact energy absorption, and spectrum gap regulation. Understanding the intricate working mechanisms and exploring the rich dynamics of these structures necessitate the development of dynamic models. However, existing dynamic modeling methods