Mechanical Systems and Signal Processing最新文献

{"title":"The trade-off between structural control and vibration-based energy harvesting: Experimental assessment on a lightweight footbridge","authors":"Javier Naranjo-Pérez ,&nbsp;María Infantes ,&nbsp;Christian Gallegos-Calderón ,&nbsp;Javier Fernando Jiménez-Alonso","doi":"10.1016/j.ymssp.2025.112523","DOIUrl":"10.1016/j.ymssp.2025.112523","url":null,"abstract":"<div><div>This paper presents a promising trade-off strategy for simultaneous vibration control and energy harvesting in lightweight structures, addressing the increasing need for real-time and autonomous monitoring of actual civil engineering infrastructures. Sensor networks typically require a power supply for data measurement and transmission, which entails significant challenges for structures in remote areas due to battery maintenance issues. This study explores the feasibility of piezoelectric energy harvesting through an experimental campaign involving a controlled fibre-reinforced polymer footbridge equipped with a tuned mass damper. Different configurations are analysed with the aim of evaluating the novel possibility of placing the harvester on the vibration absorber, in order to leverage its relatively high amplitude and harmonic motion. Dynamic loads due to pedestrians include gait frequency variations tests, group of pedestrians and pedestrian streams. Peak response statistics are used to evaluate the harvested energy for the different configurations, highlighting the potential for optimizing energy harvester placement to maximize power output. Also, a feasibility study of the power output of the harvester device to supply energy to sensors is conducted. The methodology, experimental setup, and analysis of different configurations are detailed, with conclusions reinforcing the effectiveness of placing the harvesting device on the control device. This dual-function device concept balances vibration control and energy harvesting, presenting a practical solution for the current paradigm of structural design. This strategy is particularly relevant for footbridges, which often face high-level accelerations and vibration serviceability limit state challenges. The study underscores the potential of this approach to enhance the sustainability and efficiency of monitoring systems for civil engineering infrastructures, demonstrating significant promise for enhancing the performance of piezoelectric harvesters in operational structural vibrations, advancing towards self-powered sensors.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112523"},"PeriodicalIF":7.9,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143600607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-based identification and classification of acoustic emission signals from fracture process zones","authors":"Cang Xiong ,&nbsp;Andrew Boyd ,&nbsp;Dan Wang","doi":"10.1016/j.ymssp.2025.112556","DOIUrl":"10.1016/j.ymssp.2025.112556","url":null,"abstract":"<div><div>Since exploring the tensile properties of cementitious materials is an effective method for identifying the damage state of a structure, a concrete cylinder is conducted by an ultimate tensile test using a pressure tension machine, where the fracture processes are monitored by acoustic emission (AE) techniques. Based on the assessment of the proposed external evaluation framework, the infinite Bayesian gaussian mixture model (BGMM) achieves superior performance with high scores across various evaluation metrics, including Precision (0.9915), Recall (0.9871), F1 Score (0.9892), Jaccard Similarity (0.9892), Mutual Information (1.1875), and Fowlkes-Mallows Index (0.9902). These scores are approximately 0.2 points higher than those achieved by GMM and K-Means, highlighting its enhanced clustering capability. The infinite BGMM is therefore introduced to detect and classify the AE signals from fracture process zones (FPZs). As the analysis shows, in the frequency centroid (C-FRQ) domain, the distribution of the AE hits in a FPZ is statistically defined as a two-component Gaussian mixture model composed of a normal distribution of hits from shear cracks alongside a normal distribution from tensile cracks. Concurrently, as the applied pressure increases, the means of the C-FRQ distributions of the shear and tensile cracks within a fracture zone gradually converge.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112556"},"PeriodicalIF":7.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model-free finite-time saturated control for Active vehicle suspension systems with dead zones and external disturbances","authors":"Zengcheng Zhou ,&nbsp;Menghua Zhang ,&nbsp;David Navarro-Alarcon ,&nbsp;Xingjian Jing","doi":"10.1016/j.ymssp.2025.112542","DOIUrl":"10.1016/j.ymssp.2025.112542","url":null,"abstract":"<div><div>Active vehicle suspension systems (AVSSs) are important for transportation vehicles to improve ride comfort and maneuverability. However, practical AVSSs normally suffer from uncertain dynamics, unknown external disturbances, input saturations, and dead zones. To address these issues, a novel model-free finite-time saturated control with naturally constrained inputs is proposed for AVSSs to mitigate vibrations and improve ride comfort. Specifically, the hyperbolic function and the bound-based adaptive method are constructed to avoid input saturations. The finite-time convergence can be achieved by designing the nonsingular terminal sliding mode filter. Moreover, the proposed control is a completely model-free approach that does not require any prior knowledge of the exact model information. Therefore, this paper gives the <em>first</em> model-free finite-time saturated control solution for AVSSs that can simultaneously handle input saturations, achieve finite-time convergence, reject external disturbances and uncertain dynamics, maintain model-free structures, and overcome dead zones. The results provide a much improved version of the model-free AVSS control method in which the finite-time stability could be guaranteed with the naturally constrained control input. Various experiments demonstrate the effectiveness and robustness of the proposed algorithm with satisfactory anti-vibration performance and ride comfort (up to 96.5% and 94.8% improvement respectively compared to the passive suspension).</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112542"},"PeriodicalIF":7.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient model reduction and prediction of superharmonic resonances in frictional and hysteretic systems","authors":"Justin H. Porter,&nbsp;Matthew R.W. Brake","doi":"10.1016/j.ymssp.2025.112424","DOIUrl":"10.1016/j.ymssp.2025.112424","url":null,"abstract":"<div><div>Modern engineering structures exhibit nonlinear vibration behavior as designs are pushed to reduce weight and energy consumption. Of specific interest here, joints in assembled structures introduce friction, hysteresis, and unilateral contact resulting in nonlinear vibration effects. In many cases, it is impractical to remove jointed connections necessitating the understanding of these behaviors. This work focuses on superharmonic and internal resonances in hysteretic and jointed systems. Superharmonic resonances occur when a nonlinear system is forced at an integer fraction of a natural frequency resulting in a large (locally maximal) response at an integer multiple of the forcing frequency. When a second vibration mode simultaneously responds in resonance at the forcing frequency, the combined phenomena is termed an internal resonance. First, variable phase resonance nonlinear modes (VPRNM) is extended to track superharmonic resonances in multiple degree of freedom systems exhibiting hysteresis. Then a novel reduced order model based on VPRNM (VPRNM ROM) is proposed to reconstruct frequency response curves faster than utilizing the harmonic balance method (HBM). The VPRNM ROM is demonstrated for a 3 degree of freedom system with a 3:1 internal resonance and for the jointed Half Brake-Reuß Beam (HBRB), which exhibits a 7:1 internal resonance. For the HBRB, new experimental results are used to validate the modeling approaches, and a previously developed physics-based friction model is further validated, achieving frequency predictions within 3%. For the considered cases, VPRNM ROM construction is up to 4 times faster than HBM, and the evaluation of the VPRNM ROM is up to 780,000 times faster than HBM. Furthermore, the modeling framework provides insights into the mechanisms of superharmonic resonances in jointed structures, showing that both tangential slipping and normal direction clapping of the joint play important roles in exciting the superharmonic resonances in the HBRB.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112424"},"PeriodicalIF":7.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An adaptive ultra-narrow band filtering method based on flexible sliding band segmentation","authors":"Jian Cheng,&nbsp;Zhiheng Liu,&nbsp;Haiyang Pan,&nbsp;Jinde Zheng,&nbsp;Jinyu Tong","doi":"10.1016/j.ymssp.2025.112560","DOIUrl":"10.1016/j.ymssp.2025.112560","url":null,"abstract":"<div><div>Searching for the optimal frequency band is the key step in state feature extraction. However, the actually selected optimal frequency band is often inaccurate or the in-band noise is obvious, which greatly affects the accuracy of feature extraction. Therefore, a novel flexible filtering method is proposed in this paper to realize adaptive period impulse feature extraction, which is called adaptive sliding Ramanujan decomposition (ASRD). Firstly, ASRD method realizes the adaptive segmentation of ultra-narrow band by flexible sliding band segmentation, which not only improves the noise robustness, but also avoids the destruction of the state feature band structure. Then, a reweighted fusion index (RFI) is constructed with excellent period impulse sensitivity, interference component robustness and monotonicity, so as to evaluate the state features of ultra-narrow band sub-modes, adaptively select effective sub-modes and reconstruct period impulses. Finally, the RFI is used to determine optimal decomposition level and select the optimal elastic filter components (EFC), so as to realize the adaptive extraction of period impulses. The analysis results of simulation and experimental signal can verify the effectiveness and superiority of ASRD method.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112560"},"PeriodicalIF":7.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital twin model of a permanent magnet synchronous motor via a multiphysics-informed deep operator network","authors":"Seho Son ,&nbsp;Hyunseung Lee ,&nbsp;Dayeon Jeong ,&nbsp;Kyung ho Sun ,&nbsp;Ki-Yong Oh","doi":"10.1016/j.ymssp.2025.112561","DOIUrl":"10.1016/j.ymssp.2025.112561","url":null,"abstract":"<div><div>This paper proposes a novel integrated framework of a multiphysics-informed deep operator network (MPI-DON) for the artificial intelligence transformation of a permanent magnet synchronous motor (PMSM). The proposed framework incorporates four key features to overcome challenges in conventional neural networks, including data shortage, imbalance, and lack of generality. First, the MPI-DON leverages the architecture of a DON for surrogate modeling, enabling effective interpolation and extrapolation in untrained conditions without extensive retraining. Second, the DON is supervised by principles of multiphysics for PMSMs, including electromagnetism and structural dynamics. Hence, the MPI-DON, comprising the PI-DON for electromagnetics and PI-DON for structural dynamics, accurately predicts the multiphysics of the PMSM under various operational conditions even though limited data are available. Third, the MPI-DON is trained with virtual data from a multiphysics finite element analysis (FEA), addressing data scarcity and enabling virtual sensing capabilities to predict multiphysics responses at any location of interest. This feature is particularly effective for replicating fault conditions, which are difficult and costly to obtain experimentally. Fourth, several strategies are deployed to secure convergence during the training phase, including domain decomposition, Fourier feature embedding, and an adaptive weighting method. Quantitative evaluations demonstrate the high accuracy and robustness: RMSEs for key electromagnetic fields and torque predictions are below 3 % and 0.026 Nm, respectively, while vibration response predictions achieve relative errors of 0.23 % or less compared to FEA. Systematic analysis also confirms that four features significantly improve the accuracy, robustness, and generality of the proposed neural network when predicting the multiphysics of PMSM for both normal and faulty conditions. The practical application of the MPI-DON on the generation of virtual fault data and fault detection of bearings in a PMSM finally underscores the effectiveness of the proposed neural network. The versatility of the MPI-DON opens a new era to provide design and control-enabling solutions in future applications through artificial intelligence transformation.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112561"},"PeriodicalIF":7.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-driven identification of bandgaps in flexural metastructures using Component Mode Synthesis and FRF Based Substructuring","authors":"Hrishikesh Gosavi,&nbsp;Vijaya V.N. Sriram Malladi","doi":"10.1016/j.ymssp.2025.112470","DOIUrl":"10.1016/j.ymssp.2025.112470","url":null,"abstract":"<div><div>Metastructures, characterized by their periodic unit cells, are known for their ability to block the propagation of elastic waves within specific frequency ranges, known as “bandgaps”. To estimate the wave propagation characteristics of these systems, two primary approaches are employed: physics-based methods and data-driven techniques. Physics-based methods depend on the material properties and geometry of the unit cells, while data-driven approaches utilize experimental data, such as steady-state dynamic response data.</div><div>This study assesses the effectiveness of data-driven techniques, particularly Component Mode Synthesis (CMS) and Frequency Response Function-Based Substructuring (FBS), in identifying bandgaps in metastructures composed of multiple unit cells. The focus is on metastructures consisting of 1D beams that exhibit flexural wave behavior. Within these structures, two significant challenges arise when using frequency response functions based on out-of-plane response data: the absence of rotational degrees of freedom (dofs) and the presence of rigid-body modes. Both factors critically impact the dispersion relationship and, by extension, the bandgap estimation. Traditionally, capturing rotational dynamics has been difficult due to limitations in direct experimental measurement, necessitating the inference of rotational dofs from translational measurements. Furthermore, rigid-body modes are estimated from experimental data. To overcome these challenges, we propose the estimation of rotational dofs by curve-fitting of translational dofs. In addition, this study explores a novel approach to the estimation of rigid body modes from the modal parameters acquired using the well-known Polymax algorithm. The discussed methodologies are also applied to derive dispersion relations for infinite metastructures.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112470"},"PeriodicalIF":7.9,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An extended Chebyshev spectral method for vibration analysis of rotating cracked plates","authors":"Qizhi Mao ,&nbsp;Yukun Chen ,&nbsp;Guoyong Jin ,&nbsp;Tiangui Ye ,&nbsp;Yantao Zhang","doi":"10.1016/j.ymssp.2025.112558","DOIUrl":"10.1016/j.ymssp.2025.112558","url":null,"abstract":"<div><div>A semi-analytical model for free vibration analysis of rotating plates with cracks is developed based on an extended Chebyshev spectral method. The displacement variables of the rotating plates modeled with thick plate theory are established by a new form of improved Chebyshev series expansions composed of a standard Chebyshev series and supplementary crack functions. The crack functions are derived from the Fourier cosine series and their antisymmetric counterparts to capture the stress singularity at the crack tip. The model systematically considers the rotating effects including the rotating stiffening, rotating softening, and Coriolis force effects. The penalty function method was used to simulate the boundary conditions, and the displacement components of the cracked plate were uniformly expressed in the form of a series expansion. The vibration governing equations of the rotating cracked plate are derived based on Hamilton principle. Experimental validation of dynamic modeling of a cracked plate is conducted. The efficiency and accuracy of the proposed method are further demonstrated by comparing results with reference data, FEM simulations, and experimental data. Numerical results show that the extended Chebyshev spectral method can accurately capture the complex geometries at crack locations while maintaining the rapid convergence characteristic of traditional Chebyshev spectral methods. Findings reveal that cracks increase modal coupling, resulting in more complex natural frequencies and mode shapes.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112558"},"PeriodicalIF":7.9,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new Bayesian sparse polynomial chaos expansion based on Gaussian scale mixture prior model","authors":"Yangtian Li ,&nbsp;Yangjun Luo ,&nbsp;Zheng Zhong ,&nbsp;Jing Yu ,&nbsp;Ruiting Wang","doi":"10.1016/j.ymssp.2025.112511","DOIUrl":"10.1016/j.ymssp.2025.112511","url":null,"abstract":"<div><div>Polynomial chaos expansion (PCE) is commonly used in uncertainty quantification as a robust meta-modeling tool for engineering applications. However, its practicality is limited by the exponential increase in computational costs that arise from the use of large input variable sets. To address this issue, researchers have introduced sparse PCE surrogate models. Among the various developed methods, a notable approach is the sparse PCE based on sparse Bayesian learning, commonly referred to as Bayesian sparse polynomial chaos expansion. In this study, an innovative Bayesian sparse polynomial chaos expansion method is presented by integrating an efficient sparse Bayesian learning algorithm based on Gaussian scale mixtures into the sparse polynomial chaos expansion. The efficient sparse Bayesian learning algorithm lowers computational costs by reformulating the joint objective function. The Gaussian scale mixture prior model encompasses two sparse-inducing priors, namely the Laplace and Student’s T prior. Consequently, two versions of Bayesian sparse PCE based on this model have been developed: one using the Laplace prior and the other using the Student’s T prior. Several experiments conducted on numerical and engineering examples validate the effectiveness of the proposed methods.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112511"},"PeriodicalIF":7.9,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing vibration energy by inverted fork harvester with electromagnetic and piezoelectric effects","authors":"Qizhao He ,&nbsp;Weiyang Qin ,&nbsp;Mengjie Shang ,&nbsp;Hongsong Wang ,&nbsp;Jianan Pan","doi":"10.1016/j.ymssp.2025.112549","DOIUrl":"10.1016/j.ymssp.2025.112549","url":null,"abstract":"<div><div>In this study a hybrid scheme for harnessing vibration energy is proposed, which incorporates both electromagnetic and piezoelectric effects into a bi-stable fork-shaped harvester to increase the harvesting efficiency. This harvester consists of a fork-shaped inverted beam, three tip magnets and an iron-core coil, it can realize jumping between potential wells within a broadband frequency range. Under base excitations, the fork-shaped structure oscillates and jumps between potential wells, making the magnetic flux through the coil change dramatically and thus generating large electric output. Meanwhile, the piezoelectric material bonded to the root of fork-shaped structure deflects greatly and generates electric output through piezoelectric effect. This combination of electromagnetic and piezoelectric effects can promote the harvesting performance significantly. Theoretical analyses and simulations are carried out. The validation experiments are conducted. The experiment results prove that the hybrid energy harvester owns a wide working frequency band. The system can execute jumping between potential wells under weak random excitations and generates large outputs. For a random excitation with power spectral density (PSD) of 0.065 g²/Hz, the electromagnetic root mean square (RMS) power can reach 2.626 mW.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"229 ","pages":"Article 112549"},"PeriodicalIF":7.9,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}