Mechanical Systems and Signal Processing最新文献

{"title":"Analysis of gas foil thrust bearing considering manufacturing errors: Modeling and experiments","authors":"Jianhua Chu ,&nbsp;Siyu Wu ,&nbsp;Jiyu Wang ,&nbsp;Yuanding Wang ,&nbsp;Songtao Wang ,&nbsp;Fangcheng Xu","doi":"10.1016/j.ymssp.2025.112698","DOIUrl":"10.1016/j.ymssp.2025.112698","url":null,"abstract":"<div><div>The performance of gas film thrust bearings (GFTBs) can be affected significantly by manufacturing errors. However, there is a lack of systematic quantification methods and numerical models for these errors. This paper aims to address this situation. A simple yet effective approach has been proposed to represent the manufacturing error − pad thickness − based on real measurements of 15 sets of GFTBs. A numerical correction model has been developed to analyze the effect of the pad thickness difference on the static characteristics of GFTBs. The findings indicate that discrepancies in pad thickness can significantly reduce the bearing load capacity. Additionally, experiments were conducted to verify the accuracy of the model and to analyze the correlation among pad thickness, wear, and surface roughness. The results demonstrate a significant enhancement in pad thickness uniformity after the tests, along with an effective reduction in surface roughness, even to within 0.2 μm. This work presents a new approach to improve the accuracy of numerical modelling of GFTBs.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"232 ","pages":"Article 112698"},"PeriodicalIF":7.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817067","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 dynamic load identification method with unknown load locations using modal force reconstruction and iterative optimization","authors":"Zhengshu Wang,&nbsp;Jinhui Jiang","doi":"10.1016/j.ymssp.2025.112721","DOIUrl":"10.1016/j.ymssp.2025.112721","url":null,"abstract":"<div><div>Accurately determining the location and magnitude of dynamic loads on a structure is crucial for solving or optimizing vibration issues. However, identifying the source of vibration through direct measurement is extremely challenging. Therefore, developing a rapid and accurate method for dynamic load location identification is essential. However, achieving rapid localization of multi-point excitation in continuous systems has been challenging due to the coupling relationship of their contributions to the response. This paper presents a novel method that can simultaneously identify the location and magnitude of dynamic loads acting on the structure under multi-point excitation. A “Modal-based Dynamic Load Location Identification” framework is proposed, analyzing the influence of dynamic load locations on the structural dynamic response. The relationship between system acceleration response and modal loads is constructed using numerical integration through the Newmark explicit method, thereby determining the modal loads of various orders in the vibration system. By converting the relationship between physical space loads and modal loads, a modal load residual fitness function is established. The fitness function is iteratively optimized using genetic algorithm to determine the load location, achieving rapid localization of dynamic loads under multi-point excitation. Subsequently, the computational efficiency of dynamic load identification is analyzed. Simulation results indicate that this method reduces the identification time of dynamic loads under the condition of unknown load locations to the same order of magnitude as when the load location is known, significantly improving the computational efficiency of load location identification. Moreover, it can be effectively applied to various types of load conditions, demonstrating high accuracy and excellent robustness to noise. To further verify the performance of the algorithm in practical engineering, experimental studies on dynamic load identification were conducted on a simply supported beam system, and the results confirm that the algorithm is effective. Additionally, the influence of measurement locations and Newmark parameters on the identification accuracy is discussed.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112721"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816744","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":"Transformer model combining cross-attention and self-attention guided by damage index for pipeline damage localization based on helical guided waves","authors":"Hong Zhang ,&nbsp;Guoxiang Wang ,&nbsp;Feiyu Teng ,&nbsp;Shanshan Lv ,&nbsp;Lei Zhang ,&nbsp;Faye Zhang ,&nbsp;Mingshun Jiang","doi":"10.1016/j.ymssp.2025.112669","DOIUrl":"10.1016/j.ymssp.2025.112669","url":null,"abstract":"<div><div>The structural health monitoring technology based on ultrasonic guided waves (UGW) has broad application prospects in pipeline structural damage detection. This paper proposes a Transformer model based on damage index (DI) guidance and fusion of cross- attention and self-attention (DCAS-Transformer). Firstly, based on the principle of damage and guided waves, the DI representing the correlation between healthy signals and damaged signals is calculated and used as a weight to guide subsequent model training. This step enhances the correlation between signals and space. Secondly, based on cross-attention mechanism, a channel attention module is constructed to jointly input DI and signals into the module, achieving feature fusion and further emphasizing information related to damage. Finally, in the transformer module, based on its unique spatial attention mechanism, deep damage information extraction is achieved and damage localization is completed. The results show that the average localization error is 9.6 mm and the relative error is 1.92 %, and the proposed method performs well under different sensor layouts and noise levels. Compared with other deep learning methods, the proposed method has more stable performance and better generalization.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112669"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816742","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 energy harvesting-suppressing simulating and experimental research of a two-layer beam system by utilizing a vibration energy harvesting-suppressing module","authors":"Yuhao Zhao ,&nbsp;Xiaohong Mi ,&nbsp;Cunhong Yin ,&nbsp;Mingfei Chen ,&nbsp;Hangyu Wu","doi":"10.1016/j.ymssp.2025.112731","DOIUrl":"10.1016/j.ymssp.2025.112731","url":null,"abstract":"<div><div>Beams and their coupling structures are inevitably subjected to undesirable vibrations. Investigating vibration harvesting and suppression technologies for beams is crucial for addressing vibration-related issues encountered in engineering applications. This study explores the potential of using nonlinear energy sinks for both harvesting and suppressing the vibration energy of complex beam structures. A novel nonlinear vibration energy harvesting-suppressing module was designed for this purpose, with a coupling nonlinear energy sink as its key component. The experimental investigation, guided by theoretical analysis and the characteristics of the designed module, evaluates the vibration suppression and energy harvesting capabilities of a two-layer beam system. The results indicate that the designed module exhibits notable nonlinear behavior. Theoretical analysis reveals that the vibration energy harvesting-suppressing module can be classified into two types of devices, with their specific operational characteristics, roles, vibration suppression, and energy harvesting effects determined by the parameters of the key component. Experimental findings confirm the feasibility of the module, demonstrating its ability to simultaneously suppress and harvest vibration energy from the two-layer beam system. In conclusion, this research presents a novel vibration energy harvesting-suppressing module, offering an innovative solution for integrated vibration suppression and energy capture in engineering applications.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112731"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816743","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-Dimensional Bayesian inference for model updating with neural likelihood approximator powered by dimensionality-reducing flow-based generative model","authors":"Jice Zeng ,&nbsp;Wang-Ji Yan","doi":"10.1016/j.ymssp.2025.112688","DOIUrl":"10.1016/j.ymssp.2025.112688","url":null,"abstract":"<div><div>Bayesian model updating provides a principled approach to approximating the posterior probability density function (PDF) of model parameters using incomplete and noisy data. However, the likelihood function is usually intractable, and evaluating it remains computationally prohibitive, especially for high-dimensional structural models. In this study, a novel Bayesian model updating framework is proposed that integrates a neural likelihood approximator (NLA) with a dimensionality-reduction flow-based generative model. The aim is to efficiently estimate the PDF of model parameters. The framework employs a masked autoregressive flow combined with a surjective neural network to map high-dimensional modal data into a simpler latent space. This transformation allows for the representation of the complex likelihood function with high accuracy and reduced computational cost. Specifically, the NLA learns the mapping between a multivariate standard Gaussian distribution and complex modal data through a sequence of invertible transformations conditioned on model parameters. This task is particularly challenging in structural dynamics because modal shapes can be highly sensitive to slight changes in model parameters and are often high-dimensional, making it difficult to capture their intricate relationships with the underlying physical system. Additionally, by enabling rapid computation of the log-likelihood, the framework significantly accelerates posterior estimation through the learned NLA combined with a prior distribution via Markov Chain Monte Carlo (MCMC). The proposed method is validated through case studies on an 18-story shear building and a steel pedestrian bridge, where modal data with dimensions of 342 and 220, respectively, are predicted, and the posterior distributions of 18 and 15 model parameters are estimated. The results demonstrate the capability of the proposed method to predict complex modal shapes and provide accurate posterior estimates.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112688"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816746","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":"Bandgap mechanism and seismic wave attenuation performance of buried seismic metamaterials with double resonators","authors":"Chunfeng Zhao ,&nbsp;Zhiwei Gao ,&nbsp;Fan Kong","doi":"10.1016/j.ymssp.2025.112726","DOIUrl":"10.1016/j.ymssp.2025.112726","url":null,"abstract":"<div><div>The utilization of the band gap properties in periodic structures can control the propagation of elastic waves, leading to a focus in recent years on seismic metamaterials, but it is challenging to obtain ultrawide low-frequency bandgaps. To broaden the low-frequency band gaps, two approximately equivalent buried seismic metamaterials with double resonators (BMDR) were proposed based on theoretical derivations and analyses. The mechanisms behind band gap formation and seismic wave attenuation capabilities were thoroughly investigated and validated through finite element calculations. The results show that the BMDR can generate a low-frequency wide band gap and exhibit strong attenuation of seismic waves within the band gap range. On average, the BMDR attenuated seismic waves by approximately 80 % within the local resonance band gap and by about 40 % within the Bragg band gap without amplifying seismic responses outside these band gaps.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112726"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816745","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":"K-means aided broadband ultrasonic guided wavefield processing for damage detection in composite panels","authors":"Kai Zhu ,&nbsp;Maosen Cao ,&nbsp;Wiesław Ostachowicz ,&nbsp;Maciej Radzienski","doi":"10.1016/j.ymssp.2025.112696","DOIUrl":"10.1016/j.ymssp.2025.112696","url":null,"abstract":"<div><div>Guided wave full wavefield data have been widely used for detecting, localizing, and visualizing damage in composite structures. However, the sensitivity of detection maps to excitation wave frequency and the inefficiency caused by manual parameter selection limit their practicality. To address these challenges, this study presents a K-means aided automatic wavenumber filtering method, leveraging broadband excitation signals to identify local anomalies in composite plates. This approach eliminates the need for material parameters and specific excitation frequencies which enables the automatic generation of filter masks. The method’s effectiveness was verified through experiments and finite element simulations, using broadband and narrowband excitations on glass fiber-reinforced polymer plates with Teflon inserts of varying shapes and depths. Results demonstrated that broadband guided waves, filtered into multiple frequency bands, significantly enhance damage visualization in wavefield images compared to narrowband excitation, highlighting the robustness and efficiency of the proposed technique.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112696"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816747","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":"Multi-view camera motion compensation in bridge displacement measurement with panoramic camera","authors":"Ziyang Su ,&nbsp;Linqing Wang ,&nbsp;Jiewen Zheng ,&nbsp;Jian Zhang","doi":"10.1016/j.ymssp.2025.112717","DOIUrl":"10.1016/j.ymssp.2025.112717","url":null,"abstract":"<div><div>Ambient conditions such as wind and traffic can introduce camera motion errors in bridge displacement measurement. To compensate the motion, traditional methods use one or more cameras to track fixed reference targets, which faces limitations: single cameras have a narrow field of view, and multi-camera systems are complex, expensive, and difficult to calibrate. To address these challenges, this paper proposes a multi-view camera motion compensation method in bridge displacement measurement with panoramic camera. The main contributions include two aspects: (1) A multi-view panoramic camera is utilized to overcome field-of-view limitations and system complexity. By cube projection and independent calibration, a single panoramic camera is equivalent to a quadrature four-camera system without overlapping fields of view. (2) A motion compensation method using multi-view array targets and pose transformation matrix optimization is proposed. This method uses the refined transformation matrix and the fixed connection relationships in an equivalent four-camera system to derive a theoretical model for multi-view compensation. The model allows the use of reference targets in any direction to compensate for camera motion. The accuracy and feasibility of this method were validated through deflection measurements on a bridge scaled model and an actual bridge.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112717"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816740","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":"Modeling and simulation of three-component ground motion intensity envelope function based on conditional generative adversarial network","authors":"Jia-Wei Ding,&nbsp;Da-Gang Lu,&nbsp;Zheng-Gang Cao","doi":"10.1016/j.ymssp.2025.112703","DOIUrl":"10.1016/j.ymssp.2025.112703","url":null,"abstract":"<div><div>Artificially simulated ground motions are critical to seismic analysis of engineered structures. The ground motion intensity envelope function (IEF) defines the non-stationary characteristics and controls its duration. The three-stage intensity envelope model has been widely used in engineering applications. However, its limitations in terms of consistency of trends in horizontal and vertical changes, as well as the complexity of parameterization, hinder its further application. This study proposes a three-component ground motion intensity envelope function deep generative model (IEF-DGM) based on conditional generative adversarial network (CGAN), capable of producing high-quality IEF by considering five key condition labels: moment magnitude (M_W), Joyner-Boore distance (R_JB), shear wave velocity (V_S30), and significant durations (D_S5-75, D_S5-95). Five evaluation indicators are introduced to assess the model’s predictive accuracy. Results indicate that the proposed model effectively captures the stochastic and temporal non-stationarity of the IEF and accurately predicts the vertical component, a rarely studied area. Additionally, the model is used to simulate three-component artificial ground motion records, which closely matches the target response spectra, validating its accuracy and applicability. In conclusion, the proposed ground motion IEF-DGM provides a novel approach to simulation and prediction of ground motions with significant implications.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112703"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143806830","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":"Physics induced terahertz time-of-flight compensation method for accurate thickness measurement and full-field imaging of damage in composite","authors":"Yafei Xu ,&nbsp;Xin He ,&nbsp;Xingyu Wang ,&nbsp;Hua Zhang ,&nbsp;Xiyuan Peng ,&nbsp;Datong Liu ,&nbsp;Liuyang Zhang","doi":"10.1016/j.ymssp.2025.112709","DOIUrl":"10.1016/j.ymssp.2025.112709","url":null,"abstract":"<div><div>Accurate and efficient damage thickness estimation and imaging are critical for assessing the structural integrity of composite in service. Terahertz (THz) technique, as an advanced nondestructive testing (NDT) method, has emerged considerable potentials in the quantitative characterization of composite materials. The primary challenge in damage thickness measurement lies in precisely extracting the time-of-flight (TOF) of damage from the measured THz signal. However, existing TOF extraction methods are susceptible to the complex interferences in THz signal such as dispersion, overlaps, multiple reflection, and noise, and the performance is limited by the expert experience and prior knowledge of damage characteristics. In this work, to address these limitations, a novel physics induced THz TOF compensation method is proposed for the accurate thickness measurement and full-field imaging of damage in composite. The method leverages the propagation time difference of THz wave through the damaged and non-damaged regions, and thereby mitigating the impact of the human interventions and THz signal interferences. Initially, the improved physical propagation model of THz wave in composite is established to describe the effects lift-off distance and surface evenness of sample on THz testing performance. Subsequently, the THz TOF compensation method is developed to accurately estimate the damage thickness based on THz propagation characteristic of THz wave. In addition, a high-resolution full-field damage imaging approach is proposed, utilizing the estimated damage thickness to visualize the damage distribution across the composite structure. Overall, the proposed method provides a novel insight for the accurate damage thickness measurement under various complex scenarios in THz NDT, offering significant advancements in the automation and online monitoring of composite materials.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"231 ","pages":"Article 112709"},"PeriodicalIF":7.9,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143806829","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}