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Dynamic analysis of asymmetric piecewise linear systems

Applied Mathematics and Mechanics(English Edition) 2025年第4期46卷 633-646页

作者： Ruiliang ZHANG Yongjun SHEN Xiaotong YANG School of Mechanical Engineering Shijiazhuang Tiedao UniversityShijiazhuang050043China School of Traffic and Transportation Shijiazhuang Tiedao UniversityShijiazhuang050043China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang050043China

Piecewise linear systems are prevalent in engineering practice,and can be categorized into symmetric and asymmetric piecewise linear *** that symmetry is a special case of asymmetry,it is essential to investigate the broader model,namely the asymmetric piecewise linear *** traditional averaging method is frequently used for studying nonlinear systems,particularly symmetric piecewise linear systems,with the harmonic response of the oscillator serving as a key prerequisite for calculating steady-state ***,asymmetric systems inherently exhibit nonharmonic,asymmetric responses,rendering the traditional averaging method *** overcome this limitation,this paper introduces an improved averaging method tailored for an oscillator characterized by asymmetric gaps and *** the traditional method,which assumes a purely harmonic response,the improved averaging method redefines the system response as a superposition of a direct current(DC)term and a first harmonic ***,the DC term can be regarded as the offset induced by model ***,the DC term is treated as a slow variable function of time,with its time derivative assumed to be zero when calculating the steady-state solution,akin to the amplitude and phase in the traditional averaging *** validation demonstrates that the responses computed in both time and frequency domains with the improved averaging method exhibit greater accuracy compared with those derived from the traditional *** these improved results,the study also examines the parameter effect,stability,and bifurcation phenomena within the amplitude-frequency responses.

关键词： nonlinear vibration piecewise linear system asymmetry averaging method offset

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Research on the application of the parameter freezing precise exponential integrator in vehicle-road coupling vibration

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Applied Mathematics and Mechanics(English Edition) 2025年第2期46卷 373-390页

作者： Yu ZHANG Chao ZHANG Shaohua LI Shaopu YANG State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China Department of Engineering Mechanics Shijiazhuang Tiedao UniversityShijiazhuang 050043China Hebei Research Center of the Basic Discipline Engineering Mechanics Shijiazhuang Tiedao UniversityShijiazhuang 050043China

The vehicle-road coupling dynamics problem is a prominent issue in transportation,drawing significant attention in recent *** dynamic equations are characterized by high-dimensionality,coupling,and time-varying dynamics,making the exact solutions challenging to *** a result,numerical integration methods are typically ***,conventional methods often suffer from low computational *** address this,this paper explores the application of the parameter freezing precise exponential integrator to vehicle-road coupling *** model accounts for road roughness irregularities,incorporating all terms unrelated to the linear part into the algorithm's inhomogeneous *** general construction process of the algorithm is *** validity of numerical results is verified through approximate analytical solutions(AASs),and the advantages of this method over traditional numerical integration methods are *** parameter freezing precise exponential integrator schemes are constructed based on the Runge-Kutta framework,with the fourth-order four-stage scheme identified as the optimal *** study indicates that this method can quickly and accurately capture the dynamic system's vibration response,offering a new,efficient approach for numerical studies of high-dimensional vehicle-road coupling systems.

关键词： vehicle-road coupled dynamics dynamic response parameter freezing precise exponential integrator Newmark-βintegration

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IRT-diffusion: combined denoising diffusion probabilistic models with thermal signal processing methods for automated defect detection in composites using infrared thermography

IRT-diffusion: combined denoising diffusion probabilistic mo...

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2024 International Conference on Optical and Photonic engineering, icOPEN 2024

作者： Wei, Yanjie Zhang, Yuhang Xiao, Yao Gu, Xiaohui State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China Department of Engineering Mechanics Shijiazhuang Tiedao University Shijiazhuang050043 China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

Infrared thermography (IRT) is a reliable method for detecting defects in composites with advantages of full field, non-contact, easy operation and good visualization. Nevertheless, interpretation by experts is required to distinguish between defective and sound regions in the practical evaluation of defects, which limits the industrial applications of infrared thermography. In this study, a denoising diffusion probabilistic model (DDPM) framework named IRT-Diffusion is proposed to automatically segment defective regions in thermal images. IRT-Diffusion can reconstruct a defect segmentation image from a noisy image with standard Gaussian distribution by iteratively performing multiple denoising operations. Detection results from various traditional thermal signal processing methods are employed as input for the conditional noise predictor of IRT-Diffusion to generate more accurate defect segmentation results. The core innovation of this study is that the state-of-the-art generative model is first introduced and designed for defect identification in composites using infrared thermography. To assess the performance of IRT-Diffusion, experiments were conducted on several composites panels and compared with conditional variational autoencoder (CVAE) and conditional generative adversarial network (CGAN). The results demonstrate that the proposed method achieves superior quantitative metrics and effectively extracts defective regions. © 2025 SPIE.

关键词： Image segmentation

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Determination of defect size for composites using derivative images in pulse thermography

Determination of defect size for composites using derivative...

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2024 International Conference on Optical and Photonic engineering, icOPEN 2024

作者： Wei, Yanjie Lu, Jiashuo Xiao, Yao Gu, Xiaohui State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China Department of Engineering Mechanics Shijiazhuang Tiedao University Shijiazhuang050043 China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

Pulse thermography is a reliable method for detecting defects in composites with advantages of full field, non-contact and easy operation. However, the size determination of subsurface defects with low width-to-depth ratios using pulsed thermography is a challenging task due to the blurred defect edges in infrared thermal images caused by lateral heat diffusion. The present study explores the ability of time derivative images of infrared thermography to predict defect size. 2D thermal conduction of pulse thermography based on the virtual heat source method was analyzed to compare the temperature profile and derivative profile of defects along the diameter direction, and a size prediction method based on the derivative profile is proposed. The feasibility of the proposed method was evaluated by measuring the dimensions of the flat-bottomed holes in the composite panels. The experimental results demonstrated that the size inversion method based on derivative images brings an improvement in measuring accuracy for defects. Additionally, the influences of cooling time, defect depth, defect size and thermal properties of the material on the measurement of defect dimension are also discussed. © 2025 SPIE.

关键词： Thermography (imaging)

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Variable-length Genetic Algorithm based Blind Deconvolution for Railway Bearing Fault Diagnosis

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IEEE Sensors Journal 2025年

作者： Shi, Guangze Gu, Xiaohui Yang, Shaopu Li, Hefei Liu, Zechao Shijiazhuang Tiedao University State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang050043 China

Blind deconvolution (BD) methods have shown significant promise in machinery fault diagnosis, yet their performance remains constrained by fixed filter length and susceptibility to local optima. To tackle this problem, this paper presents a variable-length genetic algorithm (VGA) to optimize the blind filter for railway bearing fault diagnosis under complex interference. Unlike existing works, an attempt is made to determine the length and coefficients of the optimal blind filter in a general framework by introducing a cutting-splicing operator to replace the crossover to achieve chromosome length variation during the optimization iteration. Based on several popular BD approaches, including MED, MCKD, MGID, and MESSD, their variable-length optimized version, i.e. VGA-MED, VGA-MCKD, VGA-MGID, VGA-MESSD, are proposed and rigorously compared with the original version and the fix-length optimized version, i.e. GA-MED, GA-MCKD, GA-MGID, GA-MESSD by both simulated and experimental railway bearing faulty signals. The results demonstrated the effectiveness and adaptability of the novel methods in recovering fault-induced repetitive transients. Furthermore, the adaptability and generalizability of the given framework make it a robust solution for BD-based fault diagnosis in industrial applications. © 2001-2012 IEEE.

关键词： Genetic algorithms

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Study on the Mechanism of Polygonal Wear in Wheels Based on Wheel-Rail Contact Normal Force

Study on the Mechanism of Polygonal Wear in Wheels Based on ...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Zhou, Zichao Liu, Yongqiang Guo, Tao Wang, Tiecheng Huo, Wenbiao State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China School of Mechanical Engineering Shijiazhuang Tiedao University Shijiazhuang050043 China CRRC TANGSHAN CO. LTD. Tangshan063000 China

ISBN: (纸本)9789819639687

To address the issue of high-order polygonal wear in high-speed trains operating at 300 km/h, this paper investigates the influence of bogie modal vibration on the initiation and progression of such wear phenomena. The model simulation incorporates the modal vibrations of both the frame and the wheelset, while also accounting for non-Hertzian contact and track irregularity within a long-term iterative wear model, thereby enhancing its alignment with real-world operational conditions. The main conclusions are: The vibration frequency of the wheel-rail contact normal force, influenced by running speed and sleeper spacing, plays a key role in the initiation of polygonal wear. The fourth-order bending resonance of the wheelset is the primary cause of the 20th-order polygon wear and its rapid development. Suspension parameters have a significant impact on the wear index, and proper adjustment of these parameters can effectively slow the progression of polygonal wear. The findings of this paper hold theoretical value and practical significance in understanding the formation and progression mechanisms of polygonal wear, as well as in developing effective measures for its mitigation. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Railroads

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Multi-Objective Parallel Human-machine Steering Coordination Control Strategy of Intelligent Vehicles Path Tracking Based on Deep Reinforcement Learning

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Chinese Journal of mechanical engineering (English Edition) 2025年第1期38卷 1-19页

作者： Wang, Hongbo Feng, Lizhao Li, Shaohua Chen, Wuwei Zhou, Juntao School of Automotive and Transportation Engineering Hefei University of Technology Hefei230009 China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China

In the parallel steering coordination control strategy for path tracking, it is difficult to match the current driver steering model using the fixed parameters with the actual driver, and the designed steering coordination control strategy under a single objective and simple conditions is difficult to adapt to the multi-dimensional state variables’ input. In this paper, we propose a deep reinforcement learning algorithm-based multi-objective parallel human-machine steering coordination strategy for path tracking considering driver misoperation and external disturbance. Firstly, the driver steering mathematical model is constructed based on the driver preview characteristics and steering delay response, and the driver characteristic parameters are fitted after collecting the actual driver driving data. Secondly, considering that the vehicle is susceptible to the influence of external disturbances during the driving process, the Tube MPC (Tube Model Predictive Control) based path tracking steering controller is designed based on the vehicle system dynamics error model. After verifying that the driver steering model meets the driver steering operation characteristics, DQN (Deep Q-network), DDPG (Deep Deterministic Policy Gradient) and TD3 (Twin Delayed Deep Deterministic Policy Gradient) deep reinforcement learning algorithms are utilized to design a multi-objective parallel steering coordination strategy which satisfies the multi-dimensional state variables’ input of the vehicle. Finally, the tracking accuracy, lateral safety, human-machine conflict and driver steering load evaluation index are designed in different driver operation states and different road environments, and the performance of the parallel steering coordination control strategies with different deep reinforcement learning algorithms and fuzzy algorithms are compared by simulations and hardware in the loop experiments. The results show that the parallel steering collaborative strategy based on a deep

关键词： Deep reinforcement learning

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Determination of safety Rock Pillar Thickness in Karst Tunnel Based on Tunnel Face Displacement Mutation Criterion 11th

Determination of Safety Rock Pillar Thickness in Karst Tunne...

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11th International Conference on Civil engineering, ICCE 2024

作者： Lang, Zhijun Ma, Zecheng Li, Mangyuan Qiao, Haiyang China Construction Seventh Engineering Division Corp. Ltd. Zhengzhou450016 China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China School of Civil Engineering Shijiazhuang Tiedao University Shijiazhuang050043 China

ISBN: (纸本)9783031879586

During the excavation of water-rich cave tunnels, it remains crucial to establish the safe rock pillar thickness at the excavation face to define the required reinforcement measures and guarantee operational security throughout engineering processes. Many factors, including geological conditions, the extent of karst development, and the water pressure within the karst cavity, influence the thickness of the safety rock pillar in a karst tunnel. Utilizing the displacement mutation criterion of the tunnel face, the safe rock pillar thickness for the karst tunnel is quantified through finite element modeling. The methodology commences with a test of the tunnel rock's geomechanical behavior, followed by parameter calibration for the tunnel's geological envelope. Based on the experimental correction parameters, the numerical simulation of the longitudinal deformation characteristics at the karst tunnel face is carried out, ultimately identifying the critical proximity range between solution cavities and working faces that triggers interfacial displacement instabilities. The thickness of the safe rock pillar is computationally determined through displacement mutation criterion at the tunnel face, with systematic investigation revealing the thickness of the safe rock pillar and its variation law across varying geostatic stresses and hydrostatic conditions. The results show that: (1) As submersion duration increases, the surrounding rock's cohesion and internal friction angle typically demonstrate a declining trend, resulting in reduced shear strength of the rock mass. (2) Under deeply buried conditions, the precision of the stratum structure method and its convergence limitations lead to reduced accuracy in determining safe rock pillar thickness when abrupt displacement occurs at the tunnel face, particularly when the karst cavity is positioned 1 m to 4 m from the tunnel face. (3) Integrating numerical modeling with displacement anomaly criteria enhances the accuracy of saf

关键词： Convergence of numerical methods

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Analysis of Factors Affecting Vibration Response of Axle Box Bearing of High-Speed Trains

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Journal of Vibration engineering and Technologies 2025年第5期13卷 1-23页

作者： Wang, Min Yang, Shaopu Liu, Yongqiang Chen, Yanhong Zhang, Kai State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang 050043 China School of Traffic and Transportation Shijiazhuang Tiedao University Shijiazhuang 050043 China School of Mechanical Engineering Shijiazhuang Tiedao University Shijiazhuang 050043 China CRRC TANGSHAN CO. LTD Tangshan 063000 China China Water Resources Beifang Investigation Design and Research Co. Ltd. Tianjin 300222 China

During the operation of high-speed trains, the vibration characteristics of axle box bearings are influenced by multiple factors. Specifically, this paper investigates the effects of track irregularity excitation, thermal deformation, and lubrication conditions on bearing vibration response under identical working conditions. To achieve this, based on Hertzian contact theory and elastohydrodynamic lubrication principles, a dynamic model of axle box bearing for high-speed train is established. Subsequently, the validity of the proposed model is verified by the experimental data of the single wheelset rolling vibration test bench. Furthermore, the typical fault forms of bearings are simulated, and consequently their effects on bearing vibration characteristics is analyzed. Moreover, the effects of fault size, rotational speed and bearing radial clearance on the system dynamic response are studied by using the eigenvalue of the covariance matrix and root mean square (RMS) value. The results show that track irregularity greatly increases bearing vibration, thermal deformation also causes bearing vibration to intensify. On the other hand, lubrication can effectively reduce bearing vibration. Additionally, the size and location of local bearing faults, along with rotational speed and radial clearance of bearings have great influence on the eigenvalue of the covariance matrix of bearing inner ring and outer ring. Correspondingly, the RMS value of bearing vibration also varies significantly under different speeds. © Springer Nature Singapore Pte Ltd. 2025.

关键词： Bearing Lubrication Thermal deformation Track irregularity

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Effects of Day-Night Temperature Fluctuations on Top-Down Cracking Development in Road structures

SSRN

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SSRN 2025年

作者： Li, Ting Qiao, Haoyu Xu, Peng Yang, Guangqing Faculty of Engineering University of Porto Porto4200 465 Portugal State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao University Shijiazhuang050043 China

Top-down cracking has become a significant issue in road structures. Temperature is a key factor in the occurrence of top-down cracking. However, there is a lack of research on how day-night temperature fluctuations impact the propagation of top-down cracking in road structures, leading to an incomplete understanding of its development. This study employs the extended finite element method, which is an innovative approach for crack analysis, to create a simulation model of road structure with top-down cracking, integrating thermal boundary theory. The model's accuracy is confirmed through comparison with previous studies. The research then examines the temperature distribution and various influential factors, including ambient temperature, material properties, and cracking characteristics, using the stress intensity factor as the main indicator. Grey relational analysis is used to further investigate the effects of different parameters on the stress intensity factor. Additionally, the study explores the propagation path of top-down cracking in road structure under cyclic temperature loading. The findings provide new insights into the thermally-induced mechanisms behind top-down cracking development in road structures. © 2025, The Authors. All rights reserved.

关键词： Road construction

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