Mechanical Systems and Signal Processing最新文献

{"title":"Temporal sparse weight based gear health monitoring tool by multichannel phase synchronized fusion dual-lifting tree model","authors":"Jing Yuan ,&nbsp;Yifeng Lu ,&nbsp;Hanlu Qian ,&nbsp;Huiming Jiang ,&nbsp;Qian Zhao ,&nbsp;Yaguo Lei","doi":"10.1016/j.ymssp.2026.113853","DOIUrl":"10.1016/j.ymssp.2026.113853","url":null,"abstract":"<div><div>Timely detection of early gear failures is a significant challenge in gear health monitoring, particularly challenging in novel gear drive systems such as planetary gears and harmonic gears. Frequency-based health indicators (HIs) are relatively less sensitive to early faults compared to time-domain approaches and inherently exhibit a delay in gear early fault warning. Meanwhile, multichannel signals inherently contain richer machine condition information compared to single channel signals. Thus, temporal sparse weight based gear health monitoring tool by multichannel phase synchronized fusion dual-lifting tree model is proposed for gear health monitoring. Multichannel phase synchronized fusion dual-lifting tree model is constructed, decomposing the raw data into several components through three levels. First, high order singular value decomposition (HOSVD) is employed, to separate noise and feature components from raw data as the 1st level of tree model. Second, multichannel phase synchronized fusion (MPSF) is proposed as the 2nd level of tree model to address phase desynchronization in full-lifecycle multichannel vibration signals, enabling linear multichannel feature fusion. It introduces multi-IMF mean phase coherence (MIMPC) for phase synchronization and compensation, producing multichannel phase synchronized feature components. Additionally, MPSF employs an estimated noise-assisted random matrix model for feature fusion, generating fused feature that integrate multichannel gear vibration signals effectively. Third, a dual-lifting transform (DLT) is proposed as the 3rd level, aimed at obtaining a dual-lifting enhanced signal to extract and quantitatively amplify early weak fault features related to faults in the fused time-domain signal. Adaptive blind deconvolution is employed as a first lifting processing to extract the gear fault features from the fused features after MPSF. Subsequently, a neighboring coefficient operator is applied to quantitatively amplify gear fault features and suppress other irrelevant residual signals. Finally, the dual-lifting enhanced signal is introduced into unified sparsity measurement framework, and the optimized temporal sparse weights are calculated by solving convex optimization for constructing temporal sparse weight based gear health indicator (TSWGHI). An experimental case of robotic harmonic reducer and an engineering case of finishing mill gearbox show that the proposed tool demonstrates remarkable performance in gear health monitoring by comparing with traditional and popular HIs.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113853"},"PeriodicalIF":8.9,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145961925","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":"Modelling and analysis of an active magnetic bearings–rotor system with coupling misalignment","authors":"Yazheng Zhao,&nbsp;Yue Zhang,&nbsp;Yuanke Li,&nbsp;Jin Zhou,&nbsp;Yang Zhou,&nbsp;Yuanping Xu","doi":"10.1016/j.ymssp.2026.113877","DOIUrl":"10.1016/j.ymssp.2026.113877","url":null,"abstract":"<div><div>Active magnetic bearings (AMBs) offer contactless support for rotor systems, making them increasingly popular in high rotational speed rotating machinery. However, when a rotor supported by AMBs is connected to the motor through a coupling, misalignment caused by manufacturing defects, assembly errors, or prolonged wear can introduce asymmetric excitation forces that degrade the system’s dynamic performance. Existing models often depend on assumed parameters with unclear physical interpretation, limiting their accuracy and applicability. Herein, an electromechanical model of the AMBs–rotor system with coupling misalignment is established, incorporating nonlinear stiffness varying over time. The uncertain parameters within the stiffness, including the static stiffness and harmonic coefficients, are identified through simulations and experimental results. Based on the model, the time and frequency domain response analyses are conducted under various parallel and angular misalignment conditions. Furthermore, the allowable safety threshold for misalignment is quantified at critical and rated rotational speeds. These findings offer valuable insights into the vibration mechanisms of AMBs–rotor systems with coupling misalignment and establish a foundation for fault diagnosis.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113877"},"PeriodicalIF":8.9,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145962591","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":"Sequential multiple importance sampling for multi-modal Bayesian inference","authors":"Binbin Li ,&nbsp;Xiao He ,&nbsp;Zihan Liao","doi":"10.1016/j.ymssp.2025.113788","DOIUrl":"10.1016/j.ymssp.2025.113788","url":null,"abstract":"<div><div>This paper introduces a sequential multiple importance sampling (SeMIS) algorithm for multimodal Bayesian inference. The method estimates Bayesian evidence using all generated samples from each proposal distribution while obtaining posterior samples through an importance-resampling scheme. A key innovation of SeMIS is the use of a softly truncated prior distribution as the intermediate proposal, providing a new way of bridging prior and posterior distributions. By enabling samples in high-likelihood regions to traverse low-probability zones, SeMIS enhances mode mixing in challenging inference problems. Comparative evaluations against subset simulation (SuS) and adaptive Bayesian updating with structural reliability methods (aBUS) demonstrate that SeMIS achieves superior performance in evidence estimation (lower bias and variance) and posterior sampling (higher effective sample sizes and closer approximation to the true posterior). The efficacy of SeMIS is further validated in a high-dimensional finite element model updating application, where it successfully localizes structural damages by quantifying stiffness loss. The proposed algorithm not only advances Bayesian computation for complex posterior distributions but also provides a robust tool for uncertainty quantification in civil engineering systems, offering new possibilities for probabilistic structural health monitoring.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113788"},"PeriodicalIF":8.9,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957028","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":"Rapid wind comfort fragility assessment at multiple levels for bridge based on physics-informed neural network","authors":"Ruiqing Han ,&nbsp;Zhipeng Li ,&nbsp;Pan Guo","doi":"10.1016/j.ymssp.2026.113867","DOIUrl":"10.1016/j.ymssp.2026.113867","url":null,"abstract":"<div><div>Train occupant comfort due to wind-induced vibration is a crucial performance for bridge wind design. The uncertainties affecting occupant comfort (e.g., wind field, aerodynamic coefficients, and structural properties) may need to be considered, which is a core requirement of performance-based wind design (PBWD). Fragility analysis is a critical tool in the PBWD theory for considering the effect of uncertainty, and it also applies to comfort assessment. However, a huge amount of samples is required to construct reliable fragility curves. To address this issue, this study proposes a rapid wind comfort fragility assessment procedure based on a physics-informed neural network (PINN) model. The PINN-based model is constructed with a hybrid neural network architecture of Transformer and Long Short-Term Memory (LSTM) as the baseline algorithm, and the dynamics differential equations (equations of motion) of the train-bridge system are integrated as physical constraints embedded in the neural network. Based on the traditional data-driven loss term, the physical residual term is introduced as a regularization constraint to enable the prediction to satisfy both the observed data distribution and the physical law. Multi-level occupant comfort grades and the corresponding thresholds are identified. For various wind intensity levels, each sample in the sample set for the uncertainty factors is input into the PINN-based model to output the dynamic acceleration response. The validity of the rapid comfort fragility assessment procedure is verified by taking a seven-span continuous girder bridge as an example. This study is helpful for the rapid assessment of multi-level comfort fragility of bridges under wind load.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113867"},"PeriodicalIF":8.9,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957025","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":"Analytic simulation of strongly non-Gaussian non-stationary stochastic processes via stochastic adaptive sparse representation based on the iterative method","authors":"Ying Zhang ,&nbsp;Wei Qu ,&nbsp;Tao Qian","doi":"10.1016/j.ymssp.2026.113884","DOIUrl":"10.1016/j.ymssp.2026.113884","url":null,"abstract":"<div><div>This paper proposes a novel method based on Stochastic Adaptive Fourier Decomposition (SAFD) for simulating non-Gaussian and non-stationary random processes with prescribed autocorrelation function (ACF) and cumulative distribution function (CDF). The method first iteratively approximates the underlying Gaussian autocorrelation matrix in the translation process, then analytically expands the target process using adaptive orthogonal basis functions. In contrast to the Karhunen–Loève (KL) expansion that requires computing eigenpairs of the autocorrelation function, SAFD directly provides an explicit analytical representation of non-Gaussian processes; compared with Hermite polynomial chaos (HermitePC), SAFD offers greater flexibility in basis function selection. Numerical experiments demonstrate that SAFD reduces approximation errors by 70%–85% compared to KL at low-order expansions (e.g., 2 or 5 terms). These results show that SAFD achieves target covariance approximation with fewer expansion terms and significantly faster convergence.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113884"},"PeriodicalIF":8.9,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957022","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":"Temperature field reconstruction and in-situ thermometry system design for the rake face in milling process","authors":"Dongqian Wang ,&nbsp;Chen Liu ,&nbsp;Yonglin Cai ,&nbsp;Uwe Teicher ,&nbsp;Albrecht Hänel ,&nbsp;Steffen Ihlenfeldt","doi":"10.1016/j.ymssp.2026.113882","DOIUrl":"10.1016/j.ymssp.2026.113882","url":null,"abstract":"<div><div>This study addresses the challenge of real-time monitoring and reconstruction of the rake face temperature field in milling. An in-situ thermometry system based on a self-powered smart toolholder is proposed. Compared to traditional battery-powered systems, the highly integrated smart toolholder achieves unlimited operation time via electromagnetic induction, with a minimum operating speed of 1150 rpm. Additionally, an embedded ultra-fine thermocouple cutter (time constant &lt; 1 ms) was developed using femtosecond laser microgroove machining and high-temperature inorganic adhesive curing processes, significantly enhancing anti-interference capability and measurement accuracy compared to infrared thermography. This effectively overcomes the technical challenge of temperature measurement at the tool-chip contact zone. Furthermore, a dynamic heat source intensity inversion model integrating the Particle Swarm Optimization (PSO) algorithm with heat diffusion theory is proposed to reconstruct the rake face temperature field based on temperature curves at measurement points. Experimental results demonstrate that the error between predicted and measured temperatures is within 13 %. The reconstructed temperature fields exhibit high consistency in peak temperature locations, with a maximum temperature error of less than 15 %. This study provides high-precision data support for thermal load analysis, tool life prediction, and process optimization in high-speed milling, contributing to the advancement of closed-loop control technology in intelligent machining.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113882"},"PeriodicalIF":8.9,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957023","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 of functionally graded twisted bilayer graphene reinforced titanium laminates for low-altitude economy aircraft","authors":"Z.H. Fu,&nbsp;W. Zhang,&nbsp;Y.F. Zhang","doi":"10.1016/j.ymssp.2026.113855","DOIUrl":"10.1016/j.ymssp.2026.113855","url":null,"abstract":"<div><div>The rapid growth of the low-altitude economy, represented by unmanned aerial vehicles (UAV), electric vertical take-off and landing (eVTOL) aircraft, and urban air mobility systems, has highlighted the urgent demand for lightweight, high-strength, and vibration-resistant structural materials. This work presents the first investigation into the nonlinear vibration and internal resonance of titanium matrix composites reinforced by twisted bilayer graphene (TBLG), aiming to advance their application in next-generation low-altitude aircraft structures. A theoretical framework is developed based on laminated plate theory and von Kármán large deformation assumptions, incorporating variable-thickness trapezoidal geometry and different functionally graded distributions of TBLG. Perturbation analysis and numerical simulations were employed to explore amplitude–frequency responses, bifurcation, and stability characteristics, while experimental tests on titanium alloy plates are conducted for validation. The results demonstrate that TBLG reinforcement substantially enhances structural stiffness, and functional grading effectively regulates natural frequencies. Furthermore, nonlinear hardening are clearly observed, consistent with theoretical predictions. This pioneering study provides new understanding of nonlinear dynamic mechanisms in TBLG–titanium composites and establishes a validated theoretical–numerical–experimental framework, offering guidance for designing lightweight and reliable structures in the low-altitude economy.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113855"},"PeriodicalIF":8.9,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957026","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 and vibration transmission of roll controlled by negative stiffness vibration absorbers","authors":"Dongping He ,&nbsp;Nan Yang ,&nbsp;Yuanming Liu ,&nbsp;Huidong Xu ,&nbsp;Guoyan Li ,&nbsp;Ziheng Duan ,&nbsp;Tao Wang","doi":"10.1016/j.ymssp.2026.113872","DOIUrl":"10.1016/j.ymssp.2026.113872","url":null,"abstract":"<div><div>The effect of vibration on rolling equipment is an internationally recognized issue in the steel rolling industry. In this study, a negative-stiffness vibration absorber (NSVA) is applied to vibration control of roll and the influence of the NSVA parameters on the nonlinear vibration characteristics from the perspective of dynamics and vibration transmission characteristics from the perspective of the energy mechanism are investigated. Considering the nonlinearity of the rolling interface, a nonlinear two-degree-of-freedom vertical vibration model is established. The vibration displacement and velocity are obtained using the incremental harmonic balance method. The amplitude-frequency characteristic equations of the main and secondary resonances are solved using the multi-scale method. We analyze how equivalent stiffness, equivalent damping, external excitation, upper roll damping on the frame, and rolling interface stiffness/damping affect amplitude-frequency curves under different resonance conditions. Using solutions at various excitation frequencies, we study how NSVA stiffness and damping impact power flow. Results show directional power flow transfer in the roll-NSVA system can effectively control the energy loss shares in the mill via NSVA parameter adjustment. In addition, the effect of NSVA vibration suppression under different reduction rates is studied experimentally. The experimental and simulation results verify the reliability of the established model and validity of the theoretical analysis.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113872"},"PeriodicalIF":8.9,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957024","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":"Bridge frequency identification from moving vehicle responses with unknown dynamic properties using an Otsu-optimized SPE algorithm","authors":"Fengli Zhou ,&nbsp;Tong Wu ,&nbsp;Zhixiang Zhou ,&nbsp;Lueqin Xu ,&nbsp;Yang Zou ,&nbsp;Xincheng Yan","doi":"10.1016/j.ymssp.2026.113869","DOIUrl":"10.1016/j.ymssp.2026.113869","url":null,"abstract":"<div><div>Identifying bridge frequencies from moving vehicle responses is often susceptible to vehicle dynamics, road roughness, and ambient noise, which can lead to spectral masking. To address this, a significant peak extraction (SPE) algorithm based on Otsu threshold optimization is proposed. First, a 3D vehicle-bridge model is developed to verify that verify that a passing vehicle excites the bridge’s modal frequencies. The proposed algorithm calculates the coherence between signals from multiple vehicle passes, determines an optimal threshold by Otsu’s method, and extracts significant peaks to identify natural frequencies of the bridge. This method enhances signal consistency, reduces non-structural interference, and improves identification accuracy. The effectiveness of the method is validated by a field test conducted on a 50-m tied-arch bridge using a heavy truck. As the number of measurement passes increases, the frequency identification becomes more accurate, with the relative error decreasing from 5.96 % to 2.46 % and RMSE stabilizing at 0.13 Hz. The results demonstrate that the proposed method can reliably extract structural frequencies without the need for specialized test vehicles or additional sensors, showing considerable potential for long-term, cost-effective structural monitoring.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113869"},"PeriodicalIF":8.9,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928306","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 digital twin solution for mixed mode I/II fatigue crack assessment under large-scale yielding","authors":"Evan Wei Wen Cheok,&nbsp;Cheng Chen,&nbsp;Xudong Qian,&nbsp;Ser Tong Quek,&nbsp;Michael Boon Ing Si","doi":"10.1016/j.ymssp.2026.113875","DOIUrl":"10.1016/j.ymssp.2026.113875","url":null,"abstract":"<div><div>This paper introduces a digital twin solution for mixed mode I/II fatigue crack assessment under large-scale yielding. Under these conditions, fatigue load magnitude significantly influences crack trajectories, unlike paths predicted by traditional linear elasticity-based criteria. Furthermore, fatigue crack growth rates under mixed mode loading may differ substantially from those under pure mode I conditions. Therefore, the proposed digital twin addresses these challenges through its diagnosis, prognosis and updating capabilities. The diagnosis component tracks the crack path under a given fatigue load magnitude and crack tip location, while remotely estimating crack size through strain data obtained from strategically placed sensors. The prognosis component computes the cyclic <em>J</em>-integral as the crack driving force using the same inputs for crack path generation. The digital twin finally establishes a high-fidelity connection with its physical counterpart by employing the unscented Kalman filter to update parameters within a fatigue crack growth rate model. This study investigates the performance of the digital twin against three specimens under constant amplitude loading and three specimens under variable amplitude loading. Under constant amplitude loading, the digital twin prognosticates the remaining useful life with the updated parameters. Whereas under variable amplitude loading, the digital twin considers load sequence effects and instead performs a fatigue reliability assessment against potential failure mechanisms. The digital twin performs well across these specimens, (1) ensuring that the observed remaining useful life falls consistently within two standard deviations of the predicted mean and (2) correctly identifying the dominant failure mechanism under both step-up and step-down loading regimes.</div></div>","PeriodicalId":51124,"journal":{"name":"Mechanical Systems and Signal Processing","volume":"245 ","pages":"Article 113875"},"PeriodicalIF":8.9,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957033","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}