Mechanical Systems and Signal Processing最新文献

{"title":"Parameter identification for stick–slip friction model and its application to dynamic analysis of mechanical system","authors":"Jiahao Ding ,&nbsp;Hongyu Wu ,&nbsp;Yuling Zhang ,&nbsp;Shaoze Yan","doi":"10.1016/j.ymssp.2025.112626","DOIUrl":"10.1016/j.ymssp.2025.112626","url":null,"abstract":"<div><div>Stick-slip friction (SSF), as an interesting dynamic behavior, is widely presented in mechanical systems, and has a significant effect on the mechanical systems’ lifespan and operation accuracy. Accurate SSF models are crucial for the effective evaluation of the dynamic performance of mechanical systems. Therefore, this paper focuses on proposing the parameter identification method for SSF models to ensure their simulation accuracy. The typical spring-block model is used for this work, which can reflect the coupling relationship between friction force and systems’ deformation. The corresponding experimental system is established to measure the characteristic values of SSF. Then, the optimization calculation-based parameter identification is carried out. The key input parameters of the SSF model are defined as design variables, and the optimization objective is to minimize the error between experimental and simulation results. Especially, multiple working conditions are considered, and the surrogate models are introduced to improve the optimization efficiency. Finally, the SSF model is fed into dynamic models of the typical mechanical system, and the dynamic responses before and after parameter identification are comparatively analyzed. This work can provide theoretical guidance for the accurate dynamic modeling of mechanical systems.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112626"},"PeriodicalIF":7.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714290","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":"Dynamical analysis of propeller rotors whirl flutter considering complex blade geometries and induced velocities","authors":"Zhihong Song ,&nbsp;Jie Hong ,&nbsp;Zhefu Yang ,&nbsp;Yitao Cao ,&nbsp;Yanhong Ma","doi":"10.1016/j.ymssp.2025.112621","DOIUrl":"10.1016/j.ymssp.2025.112621","url":null,"abstract":"<div><div>The propeller rotor, a core power component of turboprop engines, is prone to whirl flutter, a common aeroelastic issue that can lead to rotor instability and aero-engine failure. Whirl flutter analysis requires considering complex blade geometries and accurate flow velocity distributions. In this paper, a three-dimensional blade element momentum method is introduced to calculate induced velocities, thereby determining the flow velocity distributions of propellers with complex blade geometries under non-axial inflow. The calculated results show good agreement with the scaled test data. Based on these flow velocity distributions, an aerodynamic load model is established, considering the effects of rotor whirl motion. Combined with beam finite element theory, structural bending deformation is included, forming an aeroelastic model of the propeller rotor. A stability analysis method and a response analysis method under multi-frequency excitation based on linear superposition theory are proposed. The dynamical analysis of the full-scale propeller rotor is conducted, and key factors are investigated in detail. The results show that aerodynamic loads primarily cause rotor instability by weakening the first-order backward whirl mode (1B) damping. Below the instability critical speed (ICS), the rotor exhibits fundamental frequency vibrations. At ICS, the rotor is in a self-sustained vibration at 1B mode frequency. When exceeding ICS, the rotor diverges at the 1B frequency. Key factors, including support stiffness asymmetry, induced velocities, complex blade geometries, and non-axial inflow, significantly affect the damping coefficient. Ignoring these factors can lead to substantial deviations in the velocity and stiffness stability boundary and steady-state response predictions. This highlights the importance of the proposed model in whirl flutter analysis.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112621"},"PeriodicalIF":7.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714311","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":"Nonlinear vibration characteristics of turnout rails: Simulation and advanced nonlinear modal testing","authors":"Zhaoguang Zheng ,&nbsp;Jiayin Chen ,&nbsp;Jiayi Hu ,&nbsp;Jingmang Xu ,&nbsp;Taoshuo Bai ,&nbsp;Jun Lai ,&nbsp;Ping Wang","doi":"10.1016/j.ymssp.2025.112623","DOIUrl":"10.1016/j.ymssp.2025.112623","url":null,"abstract":"<div><div>The boundary conditions of turnout rails are complex, involving three types of constraints: double-sided fastening (ordinary rails), single-sided fastening (stock rails), and without fasteners (switch rails). This paper presents a systematic investigation of the nonlinear vibration characteristics of turnout rails using a combination of simulation and experimental approaches. The simulation phase utilized transient dynamics analysis to explore nonlinear behaviour, which was then validated through experimental testing with an advanced nonlinear modal testing method. This method combines response amplitude linearization theory with the hammer test technique. The key innovation of this testing method is the use of a single hammer impact for nonlinear modal testing. The method generates an FRF matrix at varying impact amplitudes, enabling quantitative analysis of nonlinear characteristics across different load levels. By combining a new coherence function algorithm with traditional algorithms, the data reliability is ensured. It does not require specialized loading equipment, significantly improving experimental convenience and making it particularly suitable for field testing in engineering applications. Both simulation and experimental results consistently show that turnout rails exhibit nonlinear vibration characteristics, especially below 100 Hz. These characteristics include amplitude dependence, softening nonlinear effects, and inertial effects at low frequencies. Rails with double-sided fastening exhibit weak nonlinearity, noticeable only when the excitation amplitude exceeds 31 kN. In contrast, rails without fasteners show the strongest nonlinearity, making them the most easily excited. The research in this paper offers insights for identifying and quantifying nonlinear characteristics in large engineering structures under complex scenarios.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112623"},"PeriodicalIF":7.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143713809","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 modeling Enabling structure full field data reconstruction by Variable fidelity data fusion","authors":"Honghai Chen ,&nbsp;Jinglong Chen ,&nbsp;Zhenxing Li ,&nbsp;Yulang Liu ,&nbsp;Jun Wang","doi":"10.1016/j.ymssp.2025.112619","DOIUrl":"10.1016/j.ymssp.2025.112619","url":null,"abstract":"<div><div>Structural health monitoring (SHM) is crucial for ensuring that structures meet operational requirements. However, monitoring large structures often requires a complex and redundant sensor array, which can hinder efficient structural verification. The challenge lies in minimizing sensor redundancy while maintaining accuracy in capturing the structure’s full-field health, particularly in static experiments where sensor placement and data alignment are critical for precise structural monitoring. To address this issue, we propose a Multi-Task Learning-based Variable Fidelity Digital Twin Modeling (MTL-VF-DTM) approach. This method leverages abundant, low-cost simulation stress data in conjunction with a limited number of challenging sensor readings to train a neural network. Additionally, a multi-task learning mechanism is incorporated to achieve stable accuracy improvements when fusing these different fidelity data types. The proposed MTL-VF-DTM framework unfolds in two phases: 1) a Convolutional Autoencoder (CAE) is pre-trained through self-supervised learning to extract features from simulation data; 2) the decoder is co-trained using both measured and simulated data via uncertainty-based multi-task learning to optimize loss weights. Experimental results from the twin modeling of the liquid rocket motor frame and one of its components demonstrate that the proposed approach can rapidly capture full-field structural responses with fewer sensors while significantly enhancing model accuracy.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112619"},"PeriodicalIF":7.9,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697485","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":"High-fidelity integrated co-simulation model for dynamic analysis of onshore wind turbines with Steel–Concrete Hybrid Tower","authors":"Dan Wang ,&nbsp;Jun Xu ,&nbsp;Zeyu He ,&nbsp;Quanfu Yu ,&nbsp;Weiwei Tang ,&nbsp;Guangling He ,&nbsp;Qiang Wu","doi":"10.1016/j.ymssp.2025.112583","DOIUrl":"10.1016/j.ymssp.2025.112583","url":null,"abstract":"<div><div>The Steel–Concrete Hybrid Tower (SCHT) structure is complex and exhibits significant nonlinear characteristics, presenting a longstanding challenge in dynamic modeling and analysis within the industry. In this study, a wind-rotor-tower integrated coupling model is established using the subsystem co-simulation method to facilitate the dynamic analysis of detailed structures. A multi-body model of the rotor and nacelle assembly is created using Simpack, while a nonlinear finite element model of the SCHT is developed in Abaqus. The co-simulation engine enables data exchange between the different solvers, allowing for detailed modeling of the tower structure while maintaining analysis efficiency. Therefore, a high-fidelity integrated co-Simulation model is established accordingly. This approach enables the nonlinear time history analysis of onshore wind turbines with SCHT under coupled wind load effects. Comparative analyses with OpenFAST validates the effectiveness of the proposed subsystem co-simulation method. Subsequently, the proposed method is used to study the dynamic response of wind turbines with SCHT, investigating their distinct behaviors. Additionally, a novel transition section is proposed to mitigate both displacement and stress amplitude in the bolts.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112583"},"PeriodicalIF":7.9,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697486","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":"Spectrum recovery of the blade tip timing signal via the block sparsity-induced Bayesian learning","authors":"Chenyu Zhang ,&nbsp;Youhong Xiao ,&nbsp;Zhicheng Xiao ,&nbsp;Liang Yu","doi":"10.1016/j.ymssp.2025.112599","DOIUrl":"10.1016/j.ymssp.2025.112599","url":null,"abstract":"<div><div>Compressive sensing (CS) emerges as a potent strategy for the recovery of blade tip timing (BTT) signal spectrum under conditions of severe undersampling. Yet, the efficacy of prevailing CS methods is contingent upon meticulous parameter tuning, limiting their flexibility across varying operational scenarios. This paper presents a novel block sparse Bayesian learning (BSBL) methodology designed to precisely reconstruct the spectra of undersampled BTT signals. By embedding block sparsity constraints within the sparse Bayesian learning (SBL) prior, the BSBL approach notably refines the feature representation of BTT signals, surpassing the capabilities of traditional techniques. The BSBL algorithm’s parameters are adaptively refined under diverse working conditions through an expectation–maximization algorithm-based iterative updating mechanism. Numerical simulations and rotating leaf disk experiments, spanning a spectrum of rotational velocities and signal-to-noise ratios (SNRs), substantiate the BSBL algorithm’s exceptional accuracy in BTT signal spectrum recovery and target frequency identification, even under heterogeneous operating conditions. Experimental results illustrate that the BSBL algorithm achieves mode frequency errors of the first two orders below 0.3 Hz and energy error rates below 10 % for rotating blades across different settings.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112599"},"PeriodicalIF":7.9,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697487","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 customized dual-transformer framework for remaining useful life prediction of mechanical systems with degraded state","authors":"Zhan Gao ,&nbsp;Weixiong Jiang ,&nbsp;Jun Wu ,&nbsp;Yuanhang Wang ,&nbsp;Haiping Zhu","doi":"10.1016/j.ymssp.2025.112611","DOIUrl":"10.1016/j.ymssp.2025.112611","url":null,"abstract":"<div><div>Remaining Useful life (RUL) prediction is important to ensure the stable operation of mechanical systems. Recently, deep learning (DL) has achieved success in RUL prediction tasks of mechanical systems. However, existing DL-based RUL prediction methods face two significant limitations: (1) they are difficult to perceive the change time from normal state to degradation state. (2) their prediction performance is limited since they fail to capture multi-term patterns in the degraded state. To address these problems, a customized dual-Transformer framework is proposed for RUL prediction of mechanical systems by considering the degraded state. First, a contrastive Transformer network is designed to learn representation discrepancy of operation state for determining uncertain change time. Moreover, a versatile Transformer network is developed to capture multi-term dependencies for RUL prediction beyond the state change point. Finally, a self-built IR experiment and IMS bearing datasets are implemented to validate the effectiveness and superiority of the proposed method. The experimental results demonstrate that our proposed method can effectively determine state change time in advance and achieve high-precision RUL prediction of mechanical systems.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112611"},"PeriodicalIF":7.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685544","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":"Stochastic model calibration with image encoding: Converting high-dimensional sequential responses into RGB images for neural network inversion","authors":"Sifeng Bi ,&nbsp;Qi Yun ,&nbsp;Yanlin Zhao ,&nbsp;Hongsen Wang","doi":"10.1016/j.ymssp.2025.112606","DOIUrl":"10.1016/j.ymssp.2025.112606","url":null,"abstract":"<div><div>This paper proposes an inverse neural network approach for stochastic model calibration, focusing on the conversion of high-dimensional system sequential responses into RGB (Red, Green, and Blue) images, which significantly enhances the efficiency of calibration processes. By encoding multi-nodal, multi-directional data sequence into RGB images and employing advanced neural network architectures, including the Visual Geometry Group (VGG) network for frequency response data and Long Short-Term Memory (LSTM) integrated with Residual Networks (ResNet) for sequential time-domain data, the proposed method effectively decodes complex structural responses into stochastic model parameters. This process eliminates the need for conventional iterative optimization or Bayesian sampling methods, reducing computational costs while maintaining high accuracy in parameter identification. Two case studies, the NASA Langley Uncertainty Quantification Challenge and a satellite finite element model calibration task, demonstrate the effectiveness of the approach. The novel encoding–decoding framework enables real-time model calibration for high-dimensional data, making it a promising solution for complex engineering systems with large scale, high-dimensional data and inevitable uncertainties.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112606"},"PeriodicalIF":7.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696663","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":"Acoustic emission source location in orthotropic steel decks based on topology-aided multi-objective optimization and A0 arrival time correction","authors":"Jia-Hao Nie ,&nbsp;Dan Li ,&nbsp;Hao Wang ,&nbsp;Tao Yu ,&nbsp;Kevin Sze Chiang Kuang","doi":"10.1016/j.ymssp.2025.112614","DOIUrl":"10.1016/j.ymssp.2025.112614","url":null,"abstract":"<div><div>Acoustic emission (AE)-based damage location in orthotropic steel decks (OSDs), typical thin-walled spatial structures, remains challenging due to the multi-solution problem induced by complex wave propagation paths. This study proposes a robust AE location method based on topology-aided multi-objective optimization and A0 arrival time correction. Here, the multi-objective optimization model is presented by fusing the location error function and modal analysis. A topology relationship is further established between objective function and vertex numbers to aid the search process, and an initial arriving component informed A0 arrival time correction strategy is brought forward for a more accurate location. Non-dominated sorting genetic algorithm II (NSGA-II) is utilized to obtain the Pareto optimal set of the optimization model and its center is determined as the estimated damage location. Experimenting on a full-scale OSD specimen proved the capability of the proposed method in accurately locating damage sources originating from both the deck plate and U-rib. It demonstrated superior performance compared to the traditional optimization-based method and counterpart method without arrival time correction.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112614"},"PeriodicalIF":7.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685479","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 novel magnet-spring synergistic orthogonal piezoelectric vibration energy harvester","authors":"Yuanbo Chen,&nbsp;Haibin Zhang,&nbsp;Guangqing Wang,&nbsp;Yanze Wu,&nbsp;Zitai Zeng,&nbsp;Jianyu Sang,&nbsp;Debao Kong","doi":"10.1016/j.ymssp.2025.112600","DOIUrl":"10.1016/j.ymssp.2025.112600","url":null,"abstract":"<div><div>The original orthogonal PVEH composed of a horizontal beam and vertical beam can produce two resonant peaks with large amplitudes. However, an anti-resonance existing between these two peaks significantly reduces the dynamic responses and energy generation. To achieve high-performance piezoelectric vibration energy harvester (PVEH) under broadband vibrations, a novel orthogonal PVEH with magnet-spring synergistic effect (MSSE) is proposed, in which a pair of repulsive magnets is placed at the orthogonal position and four parallel linear springs is fixed at the input terminal of the original orthogonal system. The MSSE brings an additional peak between these two resonant peaks, forming three resonant regions and resulting in a wide bandwidth. It also induces a sudden jump to enhance the response amplitude of the PVEH, achieving high-performance dynamic outputs. A nonlinear electromechanical model was established to describe the response behaviors with different system parameters, such as stiffness ratio (<span><math><mrow><msub><mi>r</mi><mi>k</mi></msub></mrow></math></span>), mass ratio (<span><math><mrow><msub><mi>r</mi><mi>m</mi></msub></mrow></math></span>) and magnetic distance (<span><math><mrow><mi>d</mi></mrow></math></span>). Simulations and experiments indicate that when the system parameters are <span><math><mrow><msub><mi>r</mi><mi>k</mi></msub><mo>/</mo><msub><mi>r</mi><mi>m</mi></msub><mo>=</mo><mn>4</mn></mrow></math></span> and <span><math><mrow><mi>d</mi><mo>=</mo><mn>25</mn></mrow></math></span> mm, the new PVEH can generate three resonant zones and offer effective bandwidth of 8 Hz, achieving the maximum power of 19.2 µW, 25.8 µW and 62.7 µW, respectively in the three resonant zones. Compared to the original orthogonal PVEH, the effective bandwidth has increased by 110.6 %, and the maximum power at the anti-resonant point has increased 780 times. Field application demonstrates that the proposed orthogonal PVEH can meet the power supply requirement of low-powered electronic device.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"230 ","pages":"Article 112600"},"PeriodicalIF":7.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685361","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}