Journal of Vibroengineering: Table of Contents

Comparative analysis of non-isolated and isolated structures of multi-span through arch bridges under uniform excitation

Gao, Zhonghu — 2026-02-15T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 2, 2026, p. 360-372.
Zhonghu Gao
To conduct a comparative analysis of the differences between non-isolated and isolated structures of a multi-span through arch bridge under uniform seismic excitation in different directions, a three-span continuous through concrete-filled steel tube arch bridge was selected. Using the large-scale finite element analysis software MIDAS Civil, a non-isolated model of the actual bridge and an isolated model with lead-rubber bearings added to the top of the piers were established respectively. Dynamic characteristic analysis and comparison were carried out for the two models. Three actual seismic waves were selected to apply longitudinal, transverse, and vertical seismic excitations to the two models respectively. The arch rib internal forces, displacements, and velocities of the two structural models, the maximum internal forces of the piers, the maximum acceleration of the bridge deck, and the hysteretic curves of the isolated bearings were analyzed. It is concluded that under the action of longitudinal and transverse seismic excitations, the isolated model with lead-rubber bearings exhibits a significant isolation effect.

Penetration mechanism of CPT probe in the dense sand assisted by ultrasonic vibration

Wu, Faquan — 2026-02-15T00:00:00Z

Journal of Vibroengineering, (in Press).
Faquan Wu, Zhehong Shen, Fang Zhang, Bolong Liu, Yuanlong Li, Jie Wu, Zhong Qing Chen, Yuqi Lang, Zihao Zhu, Enjie Xu, Weihong Chen, Zhongli Xu
The cone penetration test (CPT) is widely used because of its minimal soil disturbance, simplicity, low-cost and dual functionality for exploration and testing. However, conventional CPT technology encounters significant difficulty in dense sands, which limits its applicability. To address this challenges, a novel ultrasonic-assisted CPT probe was developed based on an ultrasonic-vibration drilling technique, a series of penetration tests were performed in sand with relative densities (Dr) ranging from 30 % to 90 % to quantify the effects of Dr and ultrasonic vibration on penetration resistance and particle breakage. Besides, the particle breakage mechanism of sand and interaction between probe and sand under ultrasonic vibration were revealed. The results showed that the penetration load increases with Dr. Ultrasonic vibration effectively reduced the penetration load, however, the reduction decreased from 60 % to 18 % as Dr increased from 30 % to 90 %. As Dr increases, particle breakage around the cone tip becomes more pronounced, with a higher breakage rate closer to the cone tip. Under the ultrasonic-static coupling, particle breakage was mainly caused by ultra-high-frequency impacts between particles and the cone tip, particles collided with each other, vertical and shear stress around the probe, The stress state of the sand and soil around the ultrasonic CPT probe was divided into five regions. This study introduces a novel ultrasonic vibration CPT probe, quantifies its penetration benefits in the dense sand, and reveals the particle breakage mechanisms under the ultrasonic-static coupling. The investigation will provide insights for applications of CPT in dense sands.

Study on influence of driving system suspension parameters on wheel wear in high-speed motor car

Sha, Chengyu — 2026-02-18T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 2, 2026, p. 431-449.
Chengyu Sha, Pingbo Wu, Jie Hu
Gear transmission has a non-negligible influence on the dynamic responses and wheel wear of high-speed motor cars. This work analyzes the influence of the driving system on dynamic responses and wheel wear of high-speed motor cars during acceleration. Firstly, a fully nonlinear multibody system(MBS) is developed and various nonlinear factors, such as various types of dampers and wheel-rail contact relation, are considered, and the detailed gear transmission is also introduced to obtain the accurate dynamic responses. Secondly, a wheel wear prediction model integrating the Archard wear model and the vehicle dynamics system is established based on wheel tread update strategy of target speed, and wheel wear evolution of high-speed motor car is obtained in one re-profiling cycle, and simulation results are compared with the field measured data respectively to validate vehicle model and wheel wear prediction procedure. Finally, the effects of gearbox suspension rod stiffness and vertical motor suspension joint stiffness on dynamic responses and wheel wear during acceleration process are simulated respectively. The results show that as the gearbox suspension rod stiffness increases, the gearbox suspension force gradually increases, which not only suppresses the nodding motion of the gearbox but also reduces the absolute value of the longitudinal wheel creepage, resulting in the reduction of wear depth. Moreover, the difference between the dynamic response of high-speed motor cars with and without gear transmission is huge, which indicates that gear transmission is not negligible in the process of dynamics simulation and wheel wear prediction.

Simulation data-driven intelligent fault diagnosis based on attention mechanism and transfer learning

Qiu, Xiaorong — 2026-02-20T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 2, 2026, p. 270-299.
Xiaorong Qiu, Ye Xu
In this paper, a simulation data-driven intelligent fault diagnosis algorithm based on attention mechanism and transfer learning is proposed to address insufficient fault data, low diagnostic accuracy, and inefficiency in rolling bearing monitoring under cross-condition and cross-location scenarios. To overcome the lack of real fault data, a dynamic vibration-response model is constructed through analysis of bearing and fault dynamics, generating high-fidelity fault signals across multiple operating conditions. Based on this, a diagnostic model is developed using a self-attention–assisted weighted autoencoder, where the proposed weighted autoencoder integrates a self-attention mechanism and a weight allocation mechanism and the former captures inter-feature dependencies while the latter adaptively reweighting feature contributions to enhance fault-discriminative representations. Therefore, the diagnostic model can assign corresponding weights to different importance features according to the constructed self-attention mechanism-assisted weighted self-encoding feature extraction model, effectively avoiding the problems of insufficient diagnostic accuracy and low diagnostic efficiency caused by feature redundancy and difficulty in distinguishing the importance of rolling bearing faults. Furthermore, the local maximum mean discrepancy (LMMD) method is applied to align both global and sub-domain distributions between simulated and measured data. By synthesizing cross-condition and cross-location simulated signals with real measurements, an LMMD-based intelligent transfer diagnosis model is built to enhance generalization and robustness against large distribution discrepancies. Finally, the stability and robustness of the proposed method are validated by analyzing the transfer learning performance and anti-noise disturbance ability across different operating conditions and locations.

Rolling bearing fault diagnosis under varying operating conditions using a convolutional-Transformer multi-alignment approach

Wang, Yiying — 2026-02-21T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 2, 2026, p. 219-239.
Yiying Wang, Fulu Sui, Xiaoling Li, Xiaoxin Zhang, Mingxian Liu, Chen Liu, Jie Wu
In this study, a novel deep transfer learning method, termed the Universal Domain Alignment and Multi-level Alignment Network (UDAM-Net), is established to address the significant feature distribution discrepancy between the source and target domains caused by the difficulty of feature extraction for rolling bearings under complex operating conditions. In the feature extraction stage, a one-dimensional convolutional neural network is integrated with a Transformer-based multi-head attention mechanism to effectively enhance the feature representation capability of raw signals. Additionally, the complementary advantages of Joint Maximum Mean Discrepancy (JMMD), Multi-kernel Maximum Mean Discrepancy (MK-MMD), and a domain discriminator are explored by designing a collaborative mechanism combining distribution metrics and adversarial learning in conjunction with transfer learning. Furthermore, an uncertainty-based weighting strategy is introduced to adaptively adjust the loss function and dynamically balance the contributions of different alignment modules. Finally, the Adam optimizer is employed to accelerate model convergence. Experimental results on the CWRU public dataset and a laboratory-built test rig dataset demonstrate that UDAM-Net achieves classification accuracies of 96.67 % and 96.17 %, respectively. This study enlightens fault diagnosis based on feature extraction and cross-domain feature alignment.

Active attitude control of crane hoisting system based on NMPC algorithm

Jin, Chun — 2026-02-21T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 2, 2026, p. 326-343.
Chun Jin, Shuo Qian, Zhenyu Wang, Chunyu Tian, Yanjiang Su, Shengyu Zhou, Yanhua Shen
With the rapid development of construction industrialization, modular construction has been widely applied due to its advantages such as high efficiency and environmental friendliness. As the core hoisting equipment, the crane hoisting system faces issues like poor stability and low intelligence, which have become key technical bottlenecks restricting construction efficiency. To address the above problems, this study aims at the anti-swing control of the lifting and traveling mechanism, and establishes a dynamic model of the lifting and traveling mechanism with a double-pendulum effect. Based on this model, a nonlinear model predictive controller (NMPC) is designed, followed by simulation analysis and experimental verification. The simulation results show that the designed controller can effectively suppress the load swing during the movement of the trolley (the tilt angle is controlled within ±1°) and exhibits good robustness under different working conditions. In addition, by building a scaled-down experimental platform, the accuracy of the simulation model and the actual performance of the controller are further verified. This research provides an efficient and accurate hoisting solution for improving the precision and efficiency of tower crane systems in modular building construction, and is of great significance for promoting the development of modern construction technology.

Lightweight rolling bearing fault diagnosis via dense connectivity and adaptive soft thresholding

Wang, Yanqi — 2026-02-24T00:00:00Z

Journal of Vibroengineering, (in Press).
Yanqi Wang, Songlin Zhang, Ruming Ding, Cheng Luo, Letian Zhong
Deep learning-based fault diagnosis of rolling bearings is frequently challenged by strong ambient noise in vibration signals and the high computational cost of deployable models. While deeper networks can enhance performance, they often lead to parameter redundancy and information loss in deep layers, hindering industrial application. To achieve a balance between noise robustness and model lightweightness, this paper proposes SE-SDCTNet, a novel architecture built upon Sparse Dense Compact Thresholding (SDCT) blocks and Squeeze-and-Excitation (SE) blocks. The SDCT blocks employ dense connections for efficient feature reuse, while incorporating sparsity constraints and an integrated soft-thresholding mechanism to actively suppress noise and reduce parameters. Subsequently, SE blocks adaptively recalibrate channel-wise features to compensate for potential information loss due to sparsity and to enhance discriminative power. Furthermore, dilated convolutions are embedded to preserve multi-scale contextual information throughout the network. Evaluated on the Case Western Reserve University (CWRU) bearing dataset, SE-SDCTNet demonstrates superior diagnostic accuracy (e.g., 93.1 % under severe 2 dB noise) and robustness across various signal-to-noise ratios, while containing only 0.32 million parameters, merely about 3 % of ResNet18. In summary, this work provides a lightweight, accurate, and robust solution that facilitates the transition of data-driven fault diagnosis from theoretical research to practical industrial deployment.

Optimization of seismic performance of high-rise building shear walls based on partial replacement of concrete and steel pipe reinforcement

Ma, Zhengwei — 2026-02-25T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 2, 2026, p. 344-359.
Zhengwei Ma
There are deficiencies in the optimization of the seismic performance of high-rise building shear walls, such as weak integrity and collapse resistance. Aiming at this problem, this study innovatively combines the partial replacement of concrete and steel pipe reinforcement technology, and proposes a method of locally adding steel pipe reinforcement shear walls. The experimental results showed that the specimens reinforced by the studied method exhibited better ductility and toughness when subjected to a vertical load of 840.84 kN as compared to the low-strength concrete specimens that were not reinforced by the studied method. The overall structure of the wall was able to maintain its load-bearing capacity despite the fact that the concrete at its base also suffered from crushing and spalling. In addition, the cracking displacement of the specimens (JGC-2, JGC-4, JGC-6) with localized steel pipe reinforcement was only 3.0 mm, 2.1 mm, 2.4 mm, respectively. The limit displacement was only 27.0 mm, 24.0 mm, 25.0 mm, and 45.0 mm, 47.0 mm, and 36.0 mm, respectively. The destructive displacement was only 45.0 mm, 47.0 mm, and 36.0 mm. The superiority of partial replacement of concrete and steel pipe reinforcement in improving the performance of high-rise building shear wall structures was further confirmed. It can be concluded that the research method can not only provide new ideas for the seismic strengthening of existing high-rise buildings, but also is expected to play an important role in a wider range of engineering applications. In turn, this will contribute to the improvement of the seismic performance of high-rise building structures and the protection of people's lives and property safety.

A rolling bearing fault classification method based on feature optimization and transformer-SVM

Wei, Chunxue — 2026-02-27T00:00:00Z

Journal of Vibroengineering, (in Press).
Chunxue Wei
Deep learning-based intelligent fault diagnosis methods have been widely applied in industrial production. However, in practical scenarios, the non-stationary characteristics and strong noise interference of bearing vibration signals significantly constrain the improvement of diagnostic accuracy. To address this issue, this paper proposes an intelligent fault diagnosis framework based on Variational Mode Decomposition (VMD) and Transformer-SVM. This method first employs the Osprey-Cauchy-Sparrow Search Algorithm (OCSSA), with minimum envelope entropy as the optimization objective, to adaptively determine and optimize VMD's mode number K and penalty factor α, thereby obtaining the optimal signal decomposition result. Multi-dimensional indicators are then extracted from the reconstructed signal to construct feature vectors. Subsequently, leveraging the transformer's powerful capability for modeling global dependencies, it mines the deep nonlinear relationships among features. Combined with the Support Vector Machine's strong generalization performance in classification tasks, it achieves accurate classification of bearing faults under complex operating conditions. Comparative experiments on two public datasets show that the proposed method outperforms several existing methods in terms of both classification accuracy and robustness, verifying its effectiveness and advancement.

A LabVIEW-based fault diagnosis system for offshore wind turbine planetary gearboxes

Shaohua, Dong — 2026-02-27T00:00:00Z

Journal of Vibroengineering, (in Press).
Dong Shaohua, Zhang Junhui
The rapid expansion of offshore wind energy underscores the critical need for reliable gearbox monitoring, especially for failure-prone planetary gearboxes in harsh marine environments. To address this, we propose two novel, physics-informed diagnostic parameters: the Filtered Root Mean Square (FRMS) and the Normalized Summation of the positive amplitudes of the Difference Spectrum (NSDS). These parameters enhance fault detection by isolating fault-related vibrations from healthy gearbox modulation. Furthermore, an integrated, real-time diagnosis system implementing these parameters is developed using LabVIEW. Experimental validation on a dedicated test bench demonstrates the system's effectiveness, achieving a diagnostic accuracy of 95.4 % and outperforming traditional methods. This work provides a practical and efficient solution for condition monitoring of offshore wind turbine gearboxes.

Fault diagnosis of rolling bearings based on amplitude modulation of local W transform spectrum

Ma, Zongcai — 2026-02-28T00:00:00Z

Journal of Vibroengineering, (in Press).
Zongcai Ma, Yongqi Chen, Qinge Dai, Linqiang Wu, Yitong Qin
As one of the key components of transmission and support in rotating machinery, rolling bearings will directly affect the operating status of the equipment. Therefore, scholars have proposed various methods to process its fault signals. Among them, spectral amplitude modulation (SAM) is a nonlinear filtering method that can effectively extract bearing fault characteristics. However, due to the high-intensity noise interference in the working environment of the equipment, the interference component dominates the monitoring signal, and the fault characteristics are no longer obvious or even undetectable. To solve the above problems, this paper proposes a local W transform spectral amplitude (LWTSAM) modulation method. First, the method divides the original signal into multiple narrowband signals in different frequency bands and selects the narrowband signal with the most abundant fault information among them; then, the selected narrowband signal uses a windowed Fourier transform (WFT) to obtain the amplitude in the time-frequency domain, and uses different weight indices (MO) to correct the amplitude; Finally, the modified amplitude is combined with its original phase to perform inverse window Fourier transform to obtain the modified signal and its square envelope, and the square envelope under the optimal weight is calculated using unbiased autocorrelation and information entropy to complete the local W transform spectrum amplitude modulation. In this paper, this method is verified through fault data sets. The research results show that this method can effectively reduce the interference of noise on fault diagnosis, and the fault characteristic information obtained is clearer. Compared with SAM method, Autogram method and fast spectral kurtosis diagram method, the superiority of this method is proved.

Research on integrated motion and vibration control methods for heated nozzles in space additive manufacturing equipment

Yang, Yuchen — 2026-03-03T00:00:00Z

Journal of Vibroengineering, (in Press).
Yuchen Yang, Yubin Fang
In microgravity and disturbance-rich orbital environments, the thermal nozzle of Delta-type space-based fused deposition modeling (FDM) systems is prone to trajectory deviations and vibration-induced defects, which can severely degrade the surface quality and mechanical integrity of printed parts. To address this problem, an integrated motion-vibration control strategy is proposed. The motion loop employs a classical PID controller for accurate trajectory tracking, whereas the vibration loop adopts a Filtered-X Least Mean Square (FXLMS) algorithm with a nonlinear variable step-size scheme jointly modulated by exponential decay and sinusoidal functions. The proposed step-size mechanism improves convergence behavior and robustness under time-varying disturbances by enabling fast initial adaptation while maintaining stable steady-state performance. A high-fidelity ADAMS-Simulink co-simulation platform is developed for comparative evaluation. The results show that the proposed strategy reduces micro-vibration amplitudes, improves tracking accuracy, and provides stronger robustness than fixed-step adaptive approaches, thereby offering an effective solution for high-precision space-based additive manufacturing.

Global bifurcation and circuit simulation of a soft-impacting system

Shi, Yuqing — 2026-03-03T00:00:00Z

Journal of Vibroengineering, (in Press).
Yuqing Shi, Longfei He
Considering that the dynamic analysis of mechanical systems with clearance needs to compile complex calculation programs, and high-precision numerical simulation is limited by computer performance. Dynamics of a two-degree-of-freedom system with soft impact are revealed from the perspective of equivalent circuit simulation in this paper. By using bifurcation diagrams and phase diagrams based on Poincaré mapping, as well as Lyapunov exponents, the mechanism of single-period multi-impact 1-p-p motion and chattering impact under low-frequency conditions was revealed. In the MultiSim14.0 environment, a circuit diagram equivalent to the mathematical model of the system is designed by using the addition circuit, integration circuit, and inverter circuit composed of operational amplifiers, resistors, and capacitors. The nonlinear module is realized by the saturation characteristics of the operational amplifier. It is found that the output waveform of the virtual oscilloscope has a very good agreement with that obtained from the numerical simulation. Equivalent circuit test method not only has fast operation speed and less time consumption, but also can realize real-time dynamic adjustment of parameters, which provides a reference method for the dynamic research of mechanical system with clearance.

Study on the design and structural optimization of excitation blocks for vibrators

Hong, Li — 2026-03-05T00:00:00Z

Journal of Vibroengineering, (in Press).
Li Hong, Kewen Tian, Qiang Zhang, Ning Chen, Yize Liu
The performance of vibrator-based seismic sources is fundamentally constrained by the trade-off between excitation force and motor driving power. To address this challenge, a physics-informed framework for the parametric modeling and multi-objective optimization of annular-sector eccentric blocks is proposed. Firstly, a unified geometric model is established to derive closed-form expressions for mass properties, which are then integrated into a coupled electromechanical dynamic model to link geometric configurations directly with force output and power demand. To enhance computational efficiency, an Extreme-Frequency Substitution Strategy (EFSS) is introduced to reformulate the complex full-band dynamic optimization into a simplified static problem. The primary novelty of this work is the integration of physics-based geometric modeling, electromechanical dynamics, and extreme-frequency optimization within a single analytical framework. Sobol global sensitivity analysis reveals that the outer and inner radii are the dominant design drivers, while thickness and sector angle influence performance primarily through higher-order interactions. Using the NSGA-II algorithm, an optimized design is obtained that achieves a 10.52 % reduction in average peak driving power, a 35.26 % reduction in mass, and a 56.36 % reduction in the moment of inertia, while maintaining the required excitation force. This framework provides a rigorous and energy-efficient methodology for the design of next-generation controlled seismic vibrators.

Dynamic characteristics and experimental study of rigid-flexible coupling for rail heavy-duty maintenance vehicle

Liu, Zhiyang — 2026-03-05T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 2, 2026, p. 402-415.
Zhiyang Liu, Zeyin He, Runjie Duan, Junjie Yang, Gaohua Hu
Railway large-scale maintenance vehicles are key equipment for track maintenance. To investigate their dynamic operational characteristics, a dynamics model incorporating multi-rigid-flexible coupling components was developed, and its validity was verified through full-scale vibration tests. The results indicate that: gear system excitation has a significant influence on the vibration characteristics in the X-direction and Y-direction of the vehicle system, so in the dynamic simulation model of heavy-duty maintenance vehicles, gear system excitation load must be considered. As the center distance between the drive gearbox and axle decreases, the root-mean-square value value of vibration of the axleboxes on both sides are reduced, adjusting the center distance while ensuring adequate transmission space of the bogie power axle can effectively control the vibration of the axleboxes on both sides; The vibration response of the left axlebox is always larger than that of other positions under all working conditions, indicating that the side wheel and shaft far from the driving gearbox are more prone to encounter slackness failure induced by dynamic excitation. Therefore, during design stage, it is recommended to increase the axle interference fit.

Case study on the assessment of sound barrier performance for traffic noise reduction

Anachkova, Maja — 2026-04-05T00:00:00Z

Journal of Vibroengineering, (in Press).
Maja Anachkova, Simona Domazetovska Markovska, Dejan Shishkovski, Damjan Pecioski, Anastasija Angjusheva Ignjatovska
Noise is considered a major environmental problem in urban areas, which in recent years has seriously affected people’s health and quality of life. One of the most important solutions for noise mitigation, especially for traffic noise, is the installation of noise barriers. In this paper, an assessment of the acoustic performance of noise barriers in the city of Skopje is presented. The methodology proposes using the ISO 10847:1997 indirect method (measurement technique for determining the insertion loss of a noise barrier).The experimental results from the conducted in-situ measurements have proven that the existing noise barriers, even though with different characteristics, achieve notable insertion loss across the entire noise frequency range, with significant reductions of over 10 dB in the dominant traffic noise frequency band. The research insights confirm that the noise barriers provide an effective solution for traffic noise control, but their advantage is limited against low-frequency noise components and urban noise coming from combined (human made or natural) noise sources. The results provided in this paper fill an important research gap into the noise pollution control in the city. This research provides valuable conclusions that serve as a baseline for improving urban noise action plans and development of further noise reduction strategy in the city.

Modeling and simulation of dual-frequency phase-difference ultrasound thermometry for multilayer tissue in HIFU

Dong, Hu — 2026-04-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Hu Dong, Gang Liu
In high-intensity focused ultrasound (HIFU) therapy, the differing signs of the acoustic velocity-temperature coefficients in multilayered heterogeneous tissues (such as fat-muscle) lead to inherent systematic errors in traditional single-frequency ultrasound thermometry methods and make them susceptible to motion artifacts. Therefore, this study proposes a non-invasive temperature reconstruction theory based on the relative phase difference of dual-frequency ultrasound. By establishing a multiphysics model coupling nonlinear acoustic wave propagation and the Pennes bioheat transfer equation, and using the finite-difference time-domain (FDTD) method for simulation, the performance of this method was systematically evaluated in a three-layer tissue (skin-fat-muscle) model. Simulation results show that under 20 seconds of HIFU irradiation, the focal temperature rise reached 35.3 °C; the root-mean-square error of the temperature reconstructed by the dual-frequency phase difference method was only 0.076 °C, while the error of the traditional single-frequency time-of-flight method was as high as 8.531 °C, representing an accuracy improvement of approximately 99.1 %. Furthermore, the sensitivity of the dual-frequency method to overall axial tissue displacement was only 22.2 % of that of the single-frequency method, demonstrating excellent resistance to motion artifacts. This study provides a theoretical basis and a new design paradigm for developing high-precision and robust non-invasive thermometry systems for HIFU.

Analysis of causes for increased vibrations in Francis hydroelectric generators

Yerry, Cabrera — 2026-04-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Cabrera Yerry, Velasquez Sergio, Campos Alfredo, Prada Engels, Hernandez Pedro
The present study analyzes the causes of increased vibration in Francis-type hydroelectric generators, focusing on the rotor-stator assembly and the rotor support structure (rotor spider), and considering installation and operational performance. Through comprehensive analysis of vibration histories, visual and topographic inspections, roundness measurements, alignment and magnetic-center surveys, and finite element modeling (FEM) under nominal speed and runaway speed conditions (81.8 and 175 rpm), the principal causes of elevated vibration were identified. Key findings include: fatigue fracture of the bases supporting the polar rim support block; loss of rotor-stator magnetic centering (polar rim descent up to 20 mm); and loss of rotor roundness (maximum deviation 1.7 mm). FEM revealed stress concentrations in the original design that exceed the yield strength of A-36 steel and fatigue safety factors below 1 in the critical region. These conditions produce structural imbalance and intermittent vertical forces that increase vibration – particularly during start/stop transients and in pass-through bands of natural frequencies. Bearing issues, the thrust ring flatness and the original alignments/centricities are ruled out as primary causes. The study provides a solid technical basis for corrective interventions and redesign proposals aimed at reducing vibration and improving unit reliability, and constitutes a methodological and practical reference for diagnosing and solving vibration problems in similar hydraulic machines.

A new spatial three-channel homologous information fusion method based on two-dimensional full vector spectrum and its application

Zhang, HaiBo — 2026-04-16T00:00:00Z

Journal of Vibroengineering, (in Press).
HaiBo Zhang
The two-dimensional full vector spectrum method is based on dual-channel homologous information fusion, which can only obtain the planar cross-section vibration information of a monitoring point. However, rotor vibration occurs in three-dimensional space, and it is impossible to describe the rotor's vibration conditions in three-dimensional space using only two mutually perpendicular dual-channels. Besides, this limitation may easily lead to the omission of key fault-feature information and result in misdiagnosis. A spatial three-channel homologous information fusion method is proposed to address the above issues. Firstly, the method proves that the rotor’s spatial vortex trajectory remains elliptical in three-dimensional space. Subsequently, the transformation from the spatial coordinate system to the two-dimensional plane coordinate system is achieved through quadratic coordinate transformation, and a specific mapping relationship between any point in the spatial coordinate system and its corresponding point in the two-dimensional plane coordinate system is established. Finally, based on the theory and calculation principle of the two-dimensional full vector spectrum, the extraction of spatial three-dimensional full vector spectrum feature vectors is achieved. The superiority of the spatial three-dimensional full vector spectrum over the two-dimensional full vector spectrum is verified through simulation and experiment.

Mechanical fault diagnosis method for HVCB based on IMCEEMDAN-TSG fusion algorithm

Yu, Zhihui — 2026-04-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Zhihui Yu, Chuan Lin, Chaohui Huang, Yifan Huang, Jiaman Luo
Vibration signals from high-voltage circuit breakers (HVCB) typically contain complex background noise, and traditional fault diagnosis methods often neglect the temporal relationship between vibration signals and fault characteristics. To address these issues, an IMCEEMDAN-TSG fault diagnosis model based on vibration signals is proposed. First, Pearson correlation coefficient filtering is combined to improve the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (IMCEEMDAN) for adaptive multi-resolution analysis, which effectively separates the intrinsic mode function (IMF), thereby filtering out noise contained in the signal, suppressing mode aliasing, and preserving key signal features. Secondly, a TSG hybrid algorithm is constructed by combining the Temporal Convolutional Network (TCN) embedded with the Self-Attention Mechanism (SAM) and the Gated Recurrent Unit (GRU). This architecture facilitates the parallel feature extraction of multi-channel IMF and the capture of temporal relationships, thereby deeply modeling temporal dependencies and revealing the dynamic evolution of vibration signals. Experimental results demonstrate that the proposed model achieved a fault diagnosis accuracy of 100 % on the HVCB simulation datasets, surpassing the traditional Convolutional Neural Network (CNN) by 19.07 %. Furthermore, compared with conventional algorithms, significant improvements were observed across all classification metrics, providing an accurate and reliable solution for the mechanical fault diagnosis of HVCB.

Maintenance-event-constrained vibration health index for degradation assessment of a mine main fan

Meng, Xiao — 2026-04-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Xiao Meng, Mei Wang
Reliable operation of main mine ventilation fans is essential for mine safety and production continuity. In many mines, fan condition is still judged against fixed vibration limits that do not account for changes in airflow and pressure, which can lead to frequent false alarms and ambiguous interpretation of mechanical degradation. This paper proposes a maintenance-event-constrained vibration health index (MEC-HI) that combines operating-condition modelling with long-term residual vibration analysis using SCADA-level measurements. A linear regression model is first fitted to relate bearing RMS vibration velocity to airflow, differential pressure and motor electrical quantities during confirmed healthy operating phases. The model is then used to estimate the expected vibration level and to compute condition-normalised residual vibration. Positive residuals exceeding a statistically derived tolerance are smoothed and accumulated over time within segments separated by major maintenance events, and the cumulative index is reset after bearing replacement. Unlike many health-indicator studies that rely on high-frequency waveforms or fault-specific feature engineering, the proposed framework targets practical deployment when only routine RMS and operating tags are archived. The approach is demonstrated using a three-year dataset (24,672 operating hours) from an axial-flow main fan in a large underground copper mine. The case study shows that MEC-HI captures the onset and progression of bearing degradation more clearly than raw RMS trends and suppresses load-driven false alarms, while remaining implementable with routinely available SCADA measurements. The framework can be extended to other ventilation fans and rotating machinery operating under strongly varying loads.

Fault diagnosis of gearbox based on Wilcoxon rank- sum tests and maximum amplitude selection

Lyu, Xuan — 2026-04-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Xuan Lyu, Renfeng Zhang, Shuo Feng, Xinqiang Li
This paper proposes a novel method for gearbox fault diagnosis, which is capable of identifying both single faults (either in gears or bearings) and various types of compound faults. Vibration signals collected from a test platform were employed to validate the proposed method, where five operating states were configured, including: (1) healthy state; (2) single-tooth breakage of the fixed-axis gear; (3) single-tooth breakage of the planetary gear combined with bearing rolling element damage; (4) planetary gear wear coupled with rolling bearing outer ring damage; and (5) fixed-axis gear root crack, planetary gear wear, and bearing outer ring damage. The proposed method Wilcoxon rank- sum tests and maximum amplitude selection (WTMAS) was used as feature extraction method for vibration signals of different states and to establish the training samples and test samples. The K-Nearest Neighbor (KNN) algorithm was utilized as the classifier for fault type classification and identification. Experimental results demonstrate that the average recognition rate of the proposed method for the five states reaches 95.753 %, indicating that the method exhibits high recognition accuracy for different types of faults and is thus an effective approach for gearbox fault diagnosis.

Dynamic interaction analysis of adjacent high-rise structure systems on deep soft sites

Chen, Shuping — 2026-04-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Shuping Chen, Jinwen Wu
The dynamic interaction of adjacent high-rise structures on deep soft soils was systematically investigated using advanced three-dimensional finite element modeling. Parametric analyses considered varying building spacings (10-40 m), foundation types, and soil stiffness values. Compared with isolated soil-structure interaction (SSI), the structure-soil-structure interaction (SSSI/DCI) scenario increased peak interstory drift ratios by up to 38 % and amplified maximum foundation displacement by 25 % for the closest building pairs. Dynamic coupling also resulted in a reduction of fundamental natural frequencies by as much as 15 %. The influence of soil flexibility was found to be critical; structures on softer soils experienced stronger interaction and greater seismic response amplification. The findings provide quantitative evidence and practical guidance for the seismic design of high-rise clusters in urban environments with deep soft ground.

Research on seismic performance of high-speed railway segmental assembled round-end hollow pier with energy dissipation bar

Su, Pengfei — 2026-04-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Pengfei Su, Hui Guo, Wei Wang, Hao Li
Segmental assembled piers have gained increasing attention in bridge engineering due to their superior construction efficiency, shortened construction periods, and reduced on-site wet work. However, their application in high-seismic-intensity regions remains limited because the mechanical performance of segment joints is generally weaker than that of conventional monolithic piers. This concern is particularly critical for high-speed railway bridges, which demand exceptional structural stability and seismic safety. To address this issue, energy dissipation bars were introduced into a segmental assembled round-end hollow pier to enhance its seismic resilience. A nonlinear finite element model was developed and validated against experimental results to ensure the reliability of the numerical approach. Based on the validated model, the effects of key design parameters of the energy dissipation bars were systematically investigated, and dynamic time-history analyses were conducted to evaluate seismic responses under different earthquake motions. The results demonstrate that increasing the sectional contribution ratio of the energy dissipation bars markedly improves the lateral resistance, energy dissipation capacity, and loading-unloading stiffness of the pier. However, this enhancement also results in larger residual drift angles, indicating a trade-off between seismic robustness and post-earthquake recoverability. Compared with the diameter and quantity of the bars, their arrangement shows a relatively limited influence on seismic performance. Moreover, the vibration mitigation effectiveness becomes increasingly significant with rising peak ground acceleration (PGA), achieving reduction rates exceeding 60 %. Nevertheless, severe plastic deformation and damage to the energy dissipation bars were observed under strong earthquakes, which indirectly amplify residual displacements. Additionally, the pier exhibits substantially stronger seismic responses under near-field ground motions than under far-field motions. In particular, near-field pulse-like earthquakes significantly amplify the pier-top displacement, suggesting that special design considerations are necessary when deploying such piers in near-fault regions. This study provides important insights into the seismic performance and design optimization of segmental assembled hollow piers for high-speed railways, offering valuable theoretical support and practical guidance for their application in seismic regions.

The influence of membrane air spring cord parameters on the vertical stiffness

Wang, Xufei — 2026-04-19T00:00:00Z

Journal of Vibroengineering, (in Press).
Xufei Wang, Zhiqiang Xie, Ningchao Zhang, Jinde Song
The membrane air spring possesses the advantage of variable vertical stiffness. However, under limited vertical installation space, further investigation is required to analyze how variations in the rubber airbag cord parameters influence the vertical stiffness of membrane air springs. A finite element model of a specific membrane air spring was developed. Under a compression displacement of 40 mm, the effects of parameters such as the number of rubber airbag cord layers, cord spacing, cord angle, and cord cross-sectional area on vertical stiffness were examined. The results indicate that vertical stiffness decreases with an increase in cord spacing or cord angle, but increases with greater cord cross-sectional area or number of cord layers. Subsequently, the orthogonal experimental method was applied to construct an L9 (34) orthogonal table, and the influence of the four cord parameters on the vertical stiffness of the membrane air spring under 40 mm compression displacement was analyzed. The findings revealed that vertical stiffness is least affected by cord angle and most affected by the number of cord layers. The variation trend of vertical stiffness was determined by fitting the optimal parameter combination. Finally, the combination of four cord parameters yielding the maximum vertical stiffness was evaluated when the compression displacement increased to 50 mm, providing a reference for air spring configuration design in confined spaces.

Experimental analysis and estimation of vibration frequency for airflow-induced vibration piezoelectric generators

Zou, Huajie — 2026-04-21T00:00:00Z

Journal of Vibroengineering, (in Press).
Huajie Zou, Fuhai Cai
To address the inadequacy of existing empirical formulas for estimating the vibration frequency of small airflow-induced piezoelectric generators, this study proposes a novel method for vibration frequency estimation specifically tailored to such generators. Through experimental analysis of vibration frequencies, the current expression for vibration frequency is modified to enhance the accuracy of frequency estimation for short resonators. The results indicate that the length of the resonator is the primary influencing factor. As the length increases, the frequency decreases, demonstrating an inverse relationship. The distance between the nozzle and the resonator is regarded as a secondary factor. Although there is a slight decrease in frequency as the spacing increases, its impact remains limited. Furthermore, the discrepancy between the theoretical values derived from the modified empirical frequency formula and the experimental data does not exceed 4 %, and the coefficient of determination (R2) for the modified empirical formulation is 0.9987, highlighting its reliability as an effective method for estimating vibration frequency. These conclusions may offer guidance in designing the vibration frequency and identifying essential structural parameters.

Design and research of mechanical waveguide filters based on transmission line impedance matching

Gao, Xiaolin — 2026-04-21T00:00:00Z

Journal of Vibroengineering, (in Press).
Xiaolin Gao, Xi Chen
In response to the growing demand for advanced vibration and noise suppression in high-end equipment within the manufacturing sector, this paper proposes a novel design method for mechanical waveguide filters based on transmission line impedance matching theory. By establishing a precise force-electric analogy model, this approach effectively bridges mature circuit theory with mechanical dynamics, enabling the accurate prediction and control of elastic wave propagation. To address the prevalent issue of non-stationary vibration signals in industrial applications the Fractional Fourier Transform is innovatively employed for superior time-frequency analysis. The designed dual-joint matching filter validates this methodology, exhibiting outstanding performance at a center frequency of 2500 Hz with an insertion loss of 0.8 dB and a return loss of 19.1 dB. The filter also demonstrates sharp frequency selectivity, effective stopband suppression, and stable phase response, which are critical for maintaining signal integrity in precision systems. This research, which integrates theoretical modeling, equivalent circuit analysis, and advanced signal processing, provides a robust and efficient design framework. The proposed technique offers significant practical value for the mechanical industry, presenting a viable solution to enhance the dynamic performance, operational reliability, and noise control in modern mechanical systems, with direct applicability in fields such as aerospace, precision manufacturing, and automotive engineering.

Uncertain RUL prediction for aircraft engines: an attention-based ensemble method with partial-transfer Bayesian deep learning

Zeng, Jiyan — 2026-04-21T00:00:00Z

Journal of Vibroengineering, (in Press).
Jiyan Zeng, Yaohua Tong, Yujie Cheng, Chen Lu
Accurate prediction of the remaining useful life (RUL) of aircraft engines is crucial for ensuring flight safety and optimizing maintenance strategies. However, traditional data-driven methods typically yield point estimation, failing to quantify uncertainties arising from data noise and model limitations. This study proposes an attention-based ensemble method with partial-transfer Bayesian deep learning (Att-ensembled PT-BDL) for uncertainty quantification in aircraft engine RUL prediction. The proposed method transfers weights and biases from existing point estimation deep learning models as prior knowledge to the mean values of weights and biases in Bayesian deep learning models, freezing these parameters during training to reduce trainable parameters and enhance computational efficiency. An ensemble framework, enhanced by an attention mechanism, integrates multiple models to improve prediction accuracy and uncertainty quantification performance. A case study is conducted to demonstrate the effectiveness of the proposed method with a dataset of the PHM data challenge. The experiment results show that the proposed Att-ensembled PT-BDL method can achieve a better prediction accuracy and uncertainty quantification performance in terms of root mean square error (RMSE), prediction interval coverage probability (PICP) and prediction interval normalized average width (PINAW).

A CLSTM-CNN-Attention hybrid model and its application in fault diagnosis

Liang, Yuanhui — 2026-04-21T00:00:00Z

Journal of Vibroengineering, (in Press).
Yuanhui Liang, Yuyu Zhu, Lei Wang
Autonomous underwater vehicles (AUVs) are indispensable equipments in underwater detection, surveying, and investigation. As the main power source of AUV, the accurate and timely fault diagnosis of thruster plays key role in ensuring its safe navigation. However, this task is full of challenges due to the complication, vagueness, and randomness of underwater settings. To address the issues, a hybrid diagnosis model named CLSTM-CNN-Attention is proposed, which combines convolutional long short term memory (CLSTM), convolutional neural network (CNN) and attention mechanism. Specifically, it combines an improved hybrid network to realize the connection of long-term and short-term memory (LSTM) with CNN in parallel, which can capture the time-related and space-related fault information of input signal simultaneously. At the same time, a new linear rectification function is also introduced into the hybrid model to enhance its anti-interference capability. Finally, the diagnostic performance of the hybrid model is further improved by adding attention mechanisms, which could better focus on the fused information. Experimental and comparison results indicate that the suggested approach has remarkable interference suppression capacity and surpasses other relevant methods, demonstrating good performance in fault diagnosis of AUV thruster.

Flow characteristics of large-scale Francis turbine during transient processes

He, Xiuru — 2026-04-28T00:00:00Z

Journal of Vibroengineering, (in Press).
Xiuru He, Xiangbo Liao, Qianlin Luo, Wengui Zhao, Xueli An
With the continuous establishment and improvement of the new power system, higher requirements have been imposed on the operation of large-scale hydroelectric generating units, which makes the flow inside the turbine more complex. This study employed the computational fluid dynamics (CFD) method based on the SST k-ω turbulence model to numerically simulate the internal flow field of a large Francis turbine during the load reduction transition process, and coupled an acoustic model to analyze its flow-induced noise. The results show that under a constant head, as the guide vane opening decreases (load reduces), the low-pressure and low-speed zone inside the runner expands from the blade outlet to the inlet, while the blade passage vortex and draft tube vortex in the runner gradually develop, and the flow instability increases. The noise sound pressure level shows a decreasing trend with the reduction of load, but there are still significant peaks in specific frequency bands, among which 22 Hz and 100 Hz are respectively related to blade vibration and the operational characteristics of the runner. This study reveals the correlation characteristics between the internal flow and noise of the turbine during the transition process, providing a reference basis for the safe and stable operation of the unit, vibration and noise control, and the optimization of the transition process.