Mechanical Systems and Signal Processing最新文献_第3页

Dynamic substructuring-based identification of the rivet-squeezing force

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-03-01 DOI: 10.1016/j.ymssp.2025.112487

Tim Vrtač, Miha Kodrič, Miha Pogačar, Gregor Čepon

Riveting, which involves the plastic deformation of a rivet to join components, is widely used in automotive, aerospace, and construction due to its simplicity, reliability, and ease of disassembly. Ensuring high-quality products requires End-of-Line testing of riveted joints, typically using non-destructive methods like ultrasonic testing. However, these methods do not enable the evaluation of the rivet-squeezing force, which significantly impacts the integrity and dynamic properties of the riveted joint. In this paper, an approach to indirectly evaluate the rivet-squeezing force through the identification of the joint’s dynamic properties is proposed. Using Frequency-Based Substructuring, the joint’s dynamics are decoupled from the structural assembly, isolating the influence of the squeezing force solely to the riveted joint and not the whole assembly. This method allows for the construction of a dataset of isolated joint impedances correlated with specific rivet-squeezing forces, serving as a reference dataset. The uniqueness of the proposed approach lies in its operation on joint impedances—the joint for which the squeezing force is to be determined does not need to originate from the same assembly as the dataset joints. For a structure of interest with an unknown squeezing force, the joint’s impedance is first obtained using the FBS decoupling approach. This impedance is then characterized by comparison with the reference dataset impedances to deduce the squeezing force based on a classification procedure. It is demonstrated that the proposed approach can be used to classify the rivet-squeezing force for the structure of interest and can thus be applied in the End-of-Line control of riveted joints. The proposed approach is limited only with requirement that the riveted joints share similarities in terms of material and geometry near the joints.

铆接是通过铆钉的塑性变形来连接部件，由于其简单、可靠和易于拆卸的特点，被广泛应用于汽车、航空航天和建筑领域。为确保高质量的产品，需要对铆接接头进行生产线末端检测，通常采用超声波检测等非破坏性方法。然而，这些方法无法对铆钉挤压力进行评估，而挤压力会对铆接接头的完整性和动态性能产生重大影响。本文提出了一种通过识别接头动态特性来间接评估铆接挤压力的方法。通过基于频率的子结构分析法，将铆接处的动态特性从结构装配中分离出来，从而将挤压力的影响隔离到铆接处而不是整个装配中。通过这种方法，可以建立一个与特定铆钉挤压力相关的孤立关节阻抗数据集，作为参考数据集。建议方法的独特之处在于其对关节阻抗的操作--要确定挤压力的关节不需要与数据集关节来自同一个装配体。对于具有未知挤压力的相关结构，首先使用 FBS 去耦方法获得关节阻抗。然后通过与参考数据集阻抗的比较来确定该阻抗的特征，从而根据分类程序推断出挤压力。实验证明，所提出的方法可用于对相关结构的铆钉挤压力进行分类，因此可应用于铆接接头的线端控制。所提出的方法只限于要求铆接接头在材料和接头附近的几何形状方面具有相似性。

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引用次数: 0

Inference and Quantification of Cyclostationary Impulses: A novel noise-sensitive mixed Gaussian cyclostationary model for compound fault detection

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-03-01 DOI: 10.1016/j.ymssp.2025.112501

Qing Zhang , Xiaofei Liu , Tianqi Li , Jianqing Shi , Chin-Hon Tan , Xin Zhang , Tielin Shi , Jianping Xuan

Rolling bearings are fundamental components in modern industrial systems, where real-time fault diagnosis is vital for enhancing operational safety and optimizing maintenance strategies. Traditional signal demodulation and blind deconvolution techniques are often designed to extract a single cyclostationary impulse with periodic statistics from single fault signals by filtering. However, they cannot provide quantitative confidence levels for diagnosis results, and nonlinear filtering often disrupts multiple local periods on statistics, called the quasi- and pseudo-cyclostationary properties, in handling compound fault signals. This study proposes a novel noise-sensitive mixed Gaussian cyclostationary (MGC) model, designed to model multiple cyclostationary impulses in compound fault signals under noisy conditions. Statistical derivation demonstrates that it can model and demodulate noise- and impulse-coupled systems with probabilistic, additive, and multiplicative coupling. Additionally, a standardized fault diagnosis process is proposed, using spectral correlation analysis to test the existence of cyclostationary and developing progressive likelihood ratio testing to accurately select the optimal cyclostationary period combinations for MGC modeling and compound fault diagnosis. Without the need to compare with normal signals, the method provides a quantitative statistical confidence level for diagnosis results. Extensive simulations and comparative experiments demonstrate that the method can more accurately extract different cyclostationary impulses from various compound fault combinations.

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引用次数: 0

Adaptive output feedback anti-swing control for underactuated 7-DOF rotary crane with gravitational estimation

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-03-01 DOI: 10.1016/j.ymssp.2025.112495

Gang Li , Xin Ma , Ling Yang , Jifu Li , Jianyan Tian , Yibin Li

Rotary cranes with double spherical pendulums and variable cable lengths exhibit underactuation and high nonlinearity, resulting in an open control problem. The additional challenges posed by unknown system parameters and unmeasurable velocities further complicate the anti-swing control issues for the rotary cranes. This article proposes an adaptive output feedback anti-swing controller for the underactuated seven-degree of freedom (7-DOF) rotary crane with gravitational estimation. Firstly, we establish the dynamic model for a three-dimensional rotary crane system, which has seven degrees of freedom, including boom slewing, boom luffing, payload hoisting/lowering, as well as hook and payload spherical pendulum motion. Then, by designing auxiliary signals for velocity estimation and gravity compensation, an adaptive output feedback anti-swing controller is designed with a rigorous stability analysis. As far as we known, it is the first adaptive output feedback anti-swing control strategy for 7-DOF rotary crane without needing velocity signals. Ultimately, meticulous hardware experiments are designed to rigorously evaluate both the effectiveness and the robustness of the designed controller. The adaptive output feedback anti-swing controller outperforms current state-of-the-art control methods, achieving reductions of at least 53.99% and 35.11% in the actuated actuator positioning and unactuated swing angles, respectively.

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引用次数: 0

Wear and life predictions for bearings considering simulation-to-reality variability

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-02-28 DOI: 10.1016/j.ymssp.2025.112498

Rui He , Florian König , Yifei Wang , Florian Wirsing , Zhigang Tian , Mingjian Zuo , Zhisheng Ye

Bearing wear in mechanical systems often remains unmeasurable, establishing physical simulations as the primary method for investigating wear mechanisms and remaining useful life (RUL). However, discrepancies often emerge between simulated wear and real-world observations, even under identical lubrication and operational conditions. This phenomenon, termed simulation-to-reality variability (StRV), undermines the accuracy of simulation-based wear and RUL predictions. To address this challenge, we propose a hybrid framework that characterizes StRV as an uncertainty source and incorporates stochastic processes to enhance predictive robustness. The framework utilizes multiple nonlinear autoregressive exogenous models (NARXs) to distribute uncertainty in simulated wear volumes. Additionally, a state-dependent Wiener process, induced by a neural network, is formulated to model the dynamic evolution of bearing wear. By introducing a stochastic parameter and neural network modeling, the method accounts for inherent uncertainties while leveraging data-driven insights to infer wear patterns. This approach captures the two-stage wear evolution, comprising an initial rapid running-in stage followed by a steady wear stage. Final RUL predictions are derived through Monte Carlo simulations, enabling the propagation of stochastic uncertainties embedded in the Wiener process. The bearing wear model, constructed via coupled elasto-hydrodynamic simulations and experimentally validated, demonstrates the efficacy of the proposed methodology in comparative analyses.

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引用次数: 0

A sub-structuring approach for model reduction of frictionally clamped thin-walled structures

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-02-28 DOI: 10.1016/j.ymssp.2025.112482

Patrick Hippold, Johann Gross, Malte Krack

Thin-walled structures clamped by friction joints, such as aircraft skin panels are exposed to bending–stretching coupling and frictional contact. We propose an original sub-structuring approach, where the system is divided into thin-walled and support regions, so that geometrically nonlinear behavior is relevant only in the former, and nonlinear contact behavior only in the latter. This permits to derive reduced component models, in principle, with available techniques. The Hurty-/Craig-Bampton method, combined with an interface reduction relying on an orthogonal polynomial series, is used to construct the reduction basis for each component. To model geometrically nonlinear behavior, implicit condensation is used, where an original, engineering-oriented proposition is made for the delicate scaling of the static load cases required to estimate the coefficients of the nonlinear terms. The proposed method is validated and its computational performance is assessed for the example of a plate with frictional clamping, using finite element analysis as reference. The numerical results shed light into an interesting mutual interaction: with increased amplitude, more sliding occurs in the clamping, which reduces the axial stiffness, and thus limits the extent of geometric hardening. On the other hand, the geometrically nonlinear bending–stretching deformation has an appreciable effect on the extent of frictional dissipation.

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引用次数: 0

Infinite horizon one-step MPC with linearised constraints for electrically interconnected suspension system

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-02-28 DOI: 10.1016/j.ymssp.2025.112521

Yulin Liao , Donghong Ning , Haiping Du

This research introduces a novel Infinite Horizon One-Step Model Predictive Control (IHOS-MPC) algorithm with linearised constraints, specifically designed for semi-active Electrically Interconnected Suspension (EIS) systems to enhance vehicle dynamics and comfort. The proposed control approach combines an infinite predictive horizon with a control horizon of one, significantly reducing computational complexity while maintaining efficient, real-time control performance. By integrating linearised constraints, the algorithm operates within feasible limits, minimizing computational overhead without compromising control quality. The EIS system employs electromagnetic dampers consisting of direct current motors, allowing real-time adjustments to optimise damping forces and address both vertical and roll dynamics of the vehicle. Experimental validation demonstrates that the system effectively handles various road conditions, achieving notable improvements in ride comfort and stability. This study establishes the practicality and effectiveness of the IHOS-MPC with linearised constraints in real-world applications, offering a compelling solution for advancing semi-active suspension systems in modern vehicles.

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引用次数: 0

Predicting engine oil degradation across diverse vehicles and identifying key factors 预测各种车辆的发动机机油降解情况并确定关键因素

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-02-28 DOI: 10.1016/j.ymssp.2025.112524

Takeru Omiya, Kiyoshi Hanyuda, Eiji Nagatomi

Engine oil degradation accelerates wear and corrosion in engines, leading to failures and reduced performance. Traditional maintenance methods are inefficient, either replacing oil too frequently or risking engine damage due to delayed changes. This study proposes a novel machine learning–based predictive maintenance system that accurately forecasts engine oil degradation across various vehicles using readily available vehicle information and driving data, such as engine mileage and displacement. Over four years, 820 oil sampling data were collected from 169 commercial buses and trucks to analyze engine oil properties and operational parameters. Machine learning regression models including Support Vector Machine (SVM), Random Forest (RF), and Gaussian Process Regression (GPR) were developed to predict key oil properties such as base number, conradson carbon residue, iron content, and viscosity. The GPR model demonstrated superior predictive accuracy, effectively capturing complex relationships in the data. Shapley value analysis identified engine oil usage mileage, engine displacement, total engine mileage, and monthly mileage as significant factors affecting oil degradation, while vehicle size and bus/truck type were found to have low importance. The proposed system enhances predictive maintenance by accurately predicting oil health, improving maintenance efficiency and reducing costs. This approach offers a robust solution for monitoring engine oil condition across various vehicles, ensuring optimal engine performance and longevity without the drawbacks of traditional methods.

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引用次数: 0

Bidirectionally transformed subspace cross-domain sparse representation for CFRP fatigue damage identification under different operating conditions

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-02-28 DOI: 10.1016/j.ymssp.2025.112520

Yangkun Zou , Jiande Wu , Bo Ye , Linsong Yuan , Changchun Yang

Lamb waves have been established as a reliable choice for identifying fatigue damage in carbon fiber-reinforced polymer (CFRP). In practice, Lamb wave signals are collected under both non-fatigue and fatigue loading conditions, which significantly affects the propagation of Lamb wave. Furthermore, the signal variations caused by the above two operating conditions resemble those induced by fatigue damage. These changes are mainly reflected in amplitude variations and phase shift, which complicates the accurate identification of fatigue damage states under varying loads. This paper aims to eliminate the interference of loading conditions through domain adaptation, while simultaneously identifying the fatigue damage states using sparse representation. We presented and verified an integrative bidirectionally transformed subspace cross-domain sparse representation method. In order to enhance interference elimination, signals from different loading conditions are bidirectionally transformed into a common subspace. This transformation allows for a broader adjustment range, and further minimizes the domain discrepancy. To improve the damage identification performance, we extract signal features within the subspace using sparse representation and incorporate a linear classification module. The variables for domain adaptation, sparse representation, and linear classification module, are solved in two distinct optimization steps. The robust relationship between domain adaptation and classification enhances the overall damage identification performance. The proposed method is formulated as a constrained optimization problem, and the corresponding solution strategy is precisely derived. In order to validate the proposed method, extensive experiments were conducted using NASA-published CFRP dataset. The results demonstrate that the proposed method effectively eliminates the interference of loading conditions, achieving an average damage identification accuracy of 86.57%. This outperforms other state-of-the-art models and demonstrates excellent robustness.

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引用次数: 0

Cross-scale integrated optimization of control system with multiple MR dampers for spatial torsional vibration mitigation

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-02-28 DOI: 10.1016/j.ymssp.2025.112514

Yang Yang , Zhao-Dong Xu , Xing-Huai Huang , Pei-Pei Liu , Jun Dai , Ye Shou Xu , Yao-Rong Dong , Yang Zhang

For irregular structures with spatial torsional vibrations, the application of multiple magnetorheological (MR) dampers has been proven to be an effective way of vibration control. In control systems equipped with numerous MR dampers, a critical issue is optimizing the layout of these dampers to achieve the optimal control objectives at minimal cost. Moreover, the micro-parameters of MR fluid and the macro-parameters of MR dampers significantly influence the damping effect of the control system. Consequently, it is imperative to concurrently optimize these cross-scale parameters within the MR control system. Addressing these issues, this study aims to optimize the MR damped structure in cross scales for the mitigation of torsional vibrations in spatial irregular structures, ensuring balanced vibration mitigation while minimizing the economic cost of the MR damping system. Based on the multi-factor mathematical model of MR dampers proposed in previous research, a joint simulation platform combining OpenSEES and Matlab was established. Utilizing the OpenSEES-Matlab platform and the genetic algorithm, a cross-scale integrated optimization method of the micro-parameters of the MR fluid, the size parameters of the MR dampers, as well as their layout was proposed. The efficacy and effectiveness of the proposed cross-scale integrated optimization method were validated through comparisons of experimental results of the MR fluid and MR dampers before and after optimization, and the numerical simulation results of the MR damped structure. This study provides an effective integrated optimization method for the application of MR damping systems in structural vibration control, particularly for the control of torsional vibrations in spatial irregular structures.

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引用次数: 0

Approximate response determination of nonlinear oscillators with fractional derivative elements subjected to combined periodic and evolutionary stochastic excitations

IF 7.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Mechanical Systems and Signal Processing

Pub Date : 2025-02-28 DOI: 10.1016/j.ymssp.2025.112485

Yuanjin Zhang , Shujin Li , Zixiang Zhu , Vasileios C. Fragkoulis

In this paper, an approximate analytical method is proposed to determine the response of nonlinear oscillators with fractional derivative elements subjected to combined periodic and evolutionary stochastic excitations. This is done by combining a memory-free formulation with a linearization framework to treat both the nonlinearity and the fractional derivative elements of the system. Specifically, assuming that the system response is written as the sum of a periodic and a stochastic components, the system governing equation of motion is equivalently cast into a corresponding set of a nonlinear fractional deterministic differential sub-equation and a nonlinear fractional stochastic differential sub-equation. The fractional deterministic sub-equation is subsequently transformed into a set of coupled linear equations with integer-order derivatives solely, by relying on the memory-free formulation. On the other hand, a combination of the statistical linearization and the stochastic averaging methods is employed to treat the nonlinear fractional stochastic sub-equation subjected to the evolutionary excitation. Finally, the oscillator response displacement consisting of the mean and the variance of the periodic and the stochastic response components, respectively, is obtained by solving simultaneously the set of equations derived by applying the memory-free formulation and linearization treatments. The proposed framework can treat nonlinear oscillators with fractional derivative elements subjected to combined periodic and non-stationary stochastic excitations characterized by arbitrary evolutionary power spectrum forms, even of the non-separable kind. Its accuracy and effectiveness are demonstrated by numerical examples pertaining to nonlinear oscillators with fractional derivative elements subjected to periodic and stochastic excitation described by both separable and non-separable power spectrum forms, while Monte Carlo simulation data are also used for comparison.

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引用次数: 0