Journal of Vibroengineering: Table of Contents

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.

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.

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, Vol. 28, Issue 3, 2026, p. 671-689.
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.

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.

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.

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.

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, Vol. 28, Issue 3, 2026, p. 690-704.
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.

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.

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

Liang, Yuanhui — 2026-04-21T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 3, 2026, p. 495-513.
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.

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).

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.

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

Zou, Huajie — 2026-04-21T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 3, 2026, p. 660-670.
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.

Flow characteristics of large-scale Francis turbine during transient processes

He, Xiuru — 2026-04-28T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 3, 2026, p. 705-719.
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.

Adaptive vibration-based bearing fault diagnosis for mud pumps using MSESSA-optimized variational mode decomposition

Zhang, Chao — 2026-05-08T00:00:00Z

Journal of Vibroengineering, (in Press).
Chao Zhang, Bing Wang, Zhenzhong Zhang
Mud pumps operate under harsh conditions, where strong background noise, load fluctuations, and complex excitations result in highly non-stationary vibration signals, posing significant challenges for reliable bearing fault diagnosis. To address these challenges, this study proposes an adaptive vibration-based fault diagnosis framework for mud pump bearings, utilizing variational mode decomposition optimized by a multi-strategy enhanced sparrow search algorithm (MSESSA-VMD). The proposed MSESSA incorporates sine–cosine perturbation, Cauchy mutation, and adaptive weight updating mechanisms to enhance global exploration and convergence stability. In contrast to conventional SSA-based optimization approaches, this strategy enables automatic and robust optimization of key VMD parameters, including the number of decomposition modes and the penalty factor, thereby improving decomposition quality under complex operating conditions. Fault-relevant intrinsic mode functions (IMFs) are subsequently selected based on energy-based criteria for multi-dimensional feature extraction. Intelligent fault classification is then performed using a Light Gradient Boosting Machine (LightGBM) classifier. The effectiveness of the proposed framework is first verified using the benchmark Case Western Reserve University (CWRU) bearing dataset and further validated on simulated mud pump bearing vibration signals to assess robustness under industrial-like operating conditions. Experimental results demonstrate that the proposed method achieves an average diagnostic accuracy of 96.14 %, outperforming conventional VMD-based and SSA-VMD approaches in terms of accuracy and robustness against noise and signal non-stationarity. Overall, this study presents a novel framework that integrates a multi-strategy enhanced sparrow search mechanism with adaptive VMD parameter optimization for mud pump bearing fault diagnosis, providing a robust and generalizable solution for vibration-based machinery health monitoring in complex industrial environments.

Motor bearing fault early warning model for TCN integrating multi-attention mechanisms

Liu, Taohuang — 2026-05-08T00:00:00Z

Journal of Vibroengineering, (in Press).
Taohuang Liu, Zhihua Hu, Gulizhati Hailati, Lili Tao, Yiheng Hu, Feng Ding
Aiming at the problem of limited accuracy in motor bearing fault prediction under low-frequency, low-dimensional, and imbalanced data scenarios, this paper proposes a motor bearing fault early warning model based on a temporal convolutional network that integrates multi-attention mechanisms. The model leverages these mechanisms to enhance the network's ability to model long-term dependencies and focus on critical fault features from sparse data. To validate its performance, ablation and comparative experiments were conducted on a dataset of 10,000 samples collected from a self-built test bench. The experiment results demonstrate the superiority of the proposed model. Specifically, the Multi-Attention Temporal Convolutional Network achieved a coefficient of determination of 0.9629 and a Mean Absolute Error of 0.0244, significantly outperforming the standard Temporal Convolutional Network baseline which only achieved a Mean Absolute Error of 0.1349. These results indicate the excellent performance of the proposed model in this specific data prediction scenario, providing an effective solution to practical engineering problems where high-precision sensing equipment is unavailable.

Fault diagnosis of automotive transmission bearings based on improved CNN and transformer

Huang, Zhaoming — 2026-05-15T00:00:00Z

Journal of Vibroengineering, Vol. 28, Issue 3, 2026, p. 560-580.
Zhaoming Huang, Xuhui Yang, Can Guo
To address the challenges of fault feature extraction and the weak adaptability of diagnostic models for automotive gearbox bearings under complex operating conditions, this study proposes an improved intelligent diagnostic model that integrates Convolutional Neural Networks (CNN) and Transformers with a dual-stage dynamic sparse activation and three-dimensional attention mechanism. First, to overcome the limitations of traditional CNN with fixed architectures and limited perception of multi-domain fault features, a dual-stage dynamic sparse activation mechanism is designed. It enables adaptive computation path selection based on the complexity of input features. Then, to enhance the perception of multidimensional time-frequency-phase fault information, the Hilbert transform is applied to construct a three-dimensional feature tensor containing instantaneous amplitude, frequency, and phase. A 3D self-attention module is embedded to achieve multi-domain feature fusion. Finally, the proposed method is validated using experimental data collected under various gearbox bearing fault states and operating conditions. The results show that the model achieves an accuracy of 99.73 %, with precision, recall, and F1-score of 99.64 %, 99.63 %, and 99.68 %, respectively – all outperforming state-of-the-art methods such as GDS-YOLOv5s. Moreover, the model maintains stable recognition performance under noise and variable load conditions. These findings demonstrate that the proposed approach effectively captures subtle multi-domain fault features and exhibits strong adaptability and robustness, providing a reliable solution for intelligent operation and maintenance of gearbox bearings.

Structural and process parameter optimization for rotary riveting of wheel hub bearing face teeth

Xiong, Wei — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Wei Xiong, Yong-Kun Guo, Zhong-Di Deng, Hai-Bo Zhang, Shuo Lv
The face teeth of wheel hub bearing are manufactured using a two-step rotary riveting forming process. Controlling the forming force and improving the tooth profile fullness are critical, as these factors directly affect bearing performance. This study employs DEFORM finite element simulation combined with experimental verification to analyze the influence of structural and process parameters – including blank dimensions, pre-riveting state, feed rate, spindle rotation speed, and riveting inclination angle – on the forming force and tooth profile fullness. Optimal structural and process parameters are thereby determined. The results indicate that among blank structural parameters, wall thickness has the greatest impact on tooth profile fullness, followed by inner corner radius, with outer corner radius having the least effect. Optimized blank dimensions improve profile fullness and reduce forming force. The pre-riveting state significantly influences the tooth forming process, a fully riveted state reduces axial forming force by 24.9 % compared to a non-riveted state and markedly improves profile fullness. A smaller feed rate and higher spindle speed reduce forming force and improve profile fullness, but may cause flash at the tooth outer edge. Conversely, excessive feed rate and low spindle speed reduce profile fullness. Experimental verification shows that optimized process parameters increase tooth profile fullness by 4.6 % to 96.2 % and reduce forming force by 17.8 % compared to pre-optimization conditions, confirming the effectiveness of the parameter optimization.

Near-field seismic wave attenuation and local magnitude calibration based on controlled blasting experiments

Wang, Yu — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Yu Wang, Junhao Qu, Ruifeng Liu, Zibo Wang, Qinying Wang, Kunpeng Shi, Qijie Zhou, Shiwen Xie
With the increasing depth and intensity of coal mining in China, non-natural seismic events occur more frequently, posing higher demands on mine safety and seismic monitoring. As a core parameter in earthquake monitoring and hazard assessment, precise determination of magnitude is essential for predicting and mitigating dynamic disasters. To address this, we conducted 22 controlled blasting experiments in the Weihai Port area of Shandong Province, using a combination of fixed and mobile seismic stations to systematically investigate the attenuation characteristics of near-field seismic waves and to establish a regional calibration function for local magnitude (ML). The calibration functions for both horizontal and vertical components were derived through least-squares fitting, from which the corresponding local magnitude determination formula was developed. Results from the 22 blasting events indicate good consistency of single-station magnitudes, with small deviations compared to the magnitudes determined by the Shandong Seismic Network, satisfying the required accuracy for magnitude estimation. Overall, this study establishes a calibration function applicable within 5 km of the Weihai blasting area, enhancing the consistency between magnitudes of blasting and natural earthquakes. The results provide a valuable reference for improving regional seismic monitoring systems and strengthening early warning capabilities for mine-related hazards.

Sensor placement method for crane structural health monitoring based on multi-level damage identification

Liu, Guansi — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Guansi Liu, Hui Jin, Keqin Ding
Local damages such as microcracks and corrosion in crane steel structures often exhibit strong localization and weak mode shape perturbation characteristics. Especially when the damage scale is smaller than the modal wavelength, it cannot be simply treated as an overall damage issue for identification. In response to the diverse damage modes of crane structures and the need for dense sensor placement for local identification, a sensor optimization placement method based on multi-level damage feature fusion is proposed. Firstly, structural sub-regions are divided according to the main beam diaphragms, and sensors are arranged with boundary points as key measurement points. The displacement frequency response amplitude changes before and after damage are utilized to identify damage and eliminate insensitive measurement points to complete preliminary optimization. Secondly, a displacement frequency response amplitude change matrix is constructed, and the damage signal is enhanced through cross-frequency weighted superposition to form a damage identification vector, accurately locating the damage occurrence area. Furthermore, node-level correction is performed in candidate areas based on displacement flexibility difference values, and precise localization of damage points is achieved through priority sorting of flexibility differences. Simulation results show that under the condition where corrosion damage is set in units 20739, 20762, and 20785, the maximum point of the flexibility difference damage index is located in unit 20762, which coincides with the preset damage location, verifying the effectiveness of the hierarchical placement strategy from initial damage screening to precise localization.

Dynamic response and collapse mechanisms of transmission lines under downburst-induced wind–rain loads

Shao, Guodong — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Guodong Shao, Chongyang Zhang, Yuanchao Jia, Mingxuan Zhu, Syed Hassan Farooq, Oryngozhin Yernaz, Zhengyu Ren, Siyao Zhang, Juncai Liu
As a localized high-intensity downdraft disaster, downbursts are a significant cause of wind-rain-induced damage to transmission lines. Their unique wind field characteristics make it difficult for existing design methods to comprehensively evaluate the resistance capacity of transmission lines. Current collapse analyses of transmission lines often fail to adequately consider the wind-rain field conditions during downbursts. Therefore, this study investigates the dynamic response and collapse mechanisms of transmission lines under downburst wind-rain conditions. First, a numerical simulation model is established to explore the distribution characteristics of wind and rain. A full-scale three-dimensional computational domain model is employed to simulate the wind-rain field, which is subsequently modified. The wind-rain velocity ratio is analyzed, and a fitting formula is proposed. Subsequently, combined distributed loads are applied to the transmission line to conduct parametric analyses of the dynamic response and investigate the collapse mechanisms. The results demonstrate that the computational domain model for simulating the wind-rain field is validated using relevant models, and the Vicroy model is modified for generating wind-rain loads. The horizontal velocity of raindrops does not synchronize with wind speed variations, and the proposed fitting formula for the wind-rain velocity ratio exhibits high accuracy. Downbursts significantly influence the dynamic response of the transmission tower-line system, with the most unfavorable wind attack angles, heights, rainfall intensities, and combined conditions identified. The collapse failure mode of the transmission line is characterized by initial damage and failure of diagonal members, leading to extensive structural collapse. The critical segments vary under different wind attack angles and reference heights, while rainfall has a minor impact on the collapse process. This study provides important technical insights for the wind-resistant design and safe operation of transmission lines.

Structural capacity and impact behavior of circular bridge piers strengthened by concrete jacketing

Cong, Xiaohui — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Xiaohui Cong, Yunlong Zhang, Haixia Zhao
In response to the lack of clear calculation methods for the normal section bearing capacity of circular piers strengthened by concrete jacketing in current design codes, this paper derives a calculation formula applicable to the normal section bearing capacity of strengthened circular piers under unloading conditions. The derivation is based on the relevant provisions of the Specifications for Design of Highway Reinforced Concrete and Prestressed Concrete Bridges and Culverts, incorporating the plane-section assumption and ultimate state theory. Finite element verification shows that the theoretical values agree well with the simulation results, with a maximum error of –1.55 %, and the results are conservative, meeting engineering safety requirements. In terms of impact resistance, increasing the thickness of the strengthening layer significantly enhances the pier's stiffness, reduces the displacement peak, and shortens the dynamic response time, shifting the damage mode from global damage to locally controllable damage. Parameter analysis indicates that the diameter of the main reinforcement and the spacing of the stirrups have a limited effect on the displacement response but play a key role in energy dissipation capacity: increasing the main reinforcement diameter effectively improves the total energy dissipation, while reducing the stirrup spacing enhances the confinement effect on the core concrete and improves energy dissipation efficiency. Considering both economy and construction feasibility, it is recommended to prioritize larger diameter main reinforcement and control the stirrup spacing within the range of 10-15 cm in impact-resistant design to achieve an optimal balance between performance and cost. Combined with a bridge strengthening project in Changchun, this paper summarizes key technical points, forming a theoretically complete and practically verified technical system for pier strengthening.

Dynamics and vibration analysis of a vehicle with inner axle box based on flexible wheelsets

Ma, Yufeng — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Yufeng Ma, Yunhua Huang, Xu Hu
This study systematically investigates the dynamic performance and vibration characteristics of a metro vehicle equipped with an inner axle box bogie, with a focus on the effects of wheelset structural flexibility. A rigid-flexible coupled dynamics model is constructed. For computational efficiency, the flexible wheelset within it was developed using the finite element method and subsequently condensed via substructuring techniques. The model is integrated into multi-body dynamics software SIMPACK, incorporating non-linear suspension characteristics. Parametric analysis is conducted to evaluate vehicle dynamics under varying primary vertical stiffness and operating speeds, comparing rigid and flexible wheelset configurations in terms of straight-line ride comfort, non-linear critical speed, and curve negotiation safety. The influence of wheelset flexibility, evaluated through time- and frequency-domain analysis of axle-box vibration, is found to be subtle yet statistically relevant: it slightly reduces critical speed and amplifies lateral vibrations at high speeds without inducing resonance or exceeding safety thresholds. The rigid wheelset model is deemed sufficient for basic curve negotiation and vibration analysis, whereas the flexible model is recommended for critical speed and high-speed dynamics. These findings provide theoretical support for the design and optimisation of inner axle box bogies.

Nonsingular sliding mode control method for vibration of driving motor of ship rim propulsion device

Han, Lijun — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Lijun Han, Qian Jiang
Owing to its unique structure, the driving motor of a ship’s rim propulsion device is subject to coupling effects from multiple physical fields. This makes it difficult for conventional control methods to effectively suppress vibrations caused by high-amplitude, complex harmonics, leading to poor speed and torque control performance. Therefore, a vibration suppression method based on disturbance observer combined with non singular sliding mode control is proposed. First, a disturbance observer is constructed to monitor motor torque in real time and accurately capture torque fluctuations induced by vibration. Secondly, design a non singular sliding mode controller to adaptively and quickly adjust the motor speed when vibration is detected. Finally, the quantum particle swarm algorithm, enhanced by the artificial bee colony algorithm, is used to optimize the controller parameters, thereby improving robustness and accuracy under multi-physics field coupling. The experimental results show that this method can accurately observe the motor torque and quickly stabilize the speed between 500 r/min-800 r/min under vibration state, with the smallest torque fluctuation amplitude. This result holds important scientific significance: it validates the effectiveness of nonsingular sliding mode control combined with intelligent optimization algorithms in decoupling multi-physics field interactions and suppressing complex electromagnetic excitation vibrations, offering a new control perspective for understanding motor dynamics under extreme operating conditions. In terms of application value, this method significantly enhances the dynamic response speed and steady-state accuracy of the driving motor, directly improving propulsion efficiency and maneuverability. It also effectively reduces fatigue wear on mechanical components, extends equipment life, and lowers operation and maintenance costs throughout the ship’s life cycle. In the future, we will explore integrating this control strategy with energy efficiency optimization for propulsion devices and investigate predictive vibration suppression methods based on digital twins to achieve smarter, more efficient health management of ship propulsion systems.

Hybrid smith predictor-neuroendocrine control for semi-active suspension of high-clearance agricultural sprayers

Chen, Congcong — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Congcong Chen, Weiwei Song, Gang Li, Yuling Ye, Junfeng An
. In order to attain time-lag dynamic compensation control and decrease time-lag influence of high-clearance sprayer semi-active suspensions, a novel suspension intelligent controller based on improved Smith prediction neuroendocrine algorithm is proposed. Firstly, the time-lag semi-active suspension dynamic model of high-clearance sprayers is established, the neuroendocrine intelligent controller is designed combined with the hormone regulation mechanism in the organism. Then, by combining enhanced Smith prediction compensation controller with neuroendocrine intelligent controller, a kind of high-clearance sprayer semi-active suspension intelligent controller based on the improved Smith prediction neuroendocrine algorithm is developed. The research results show the proposed algorithm can significantly reduce body vertical acceleration (BVA) and tire dynamic load (TDL) indicators of high-clearance sprayer semi-active suspensions, effectively improve smoothness and road friendliness of sprayers, significantly enhance comprehensive performance, show strong adaptability and robustness under working conditions, and is very suitable for vibration control of the high-clearance sprayer semi-active suspension with high order time-varying, complex nonlinear and strong coupling.

A review of bridge resilience: assessment frameworks, intelligent algorithms, and future directions

Zhou, Jiuqing — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Jiuqing Zhou, Mingyou Chen, Leifa Li, Guanghui Zhang, Daming Lin
Bridge resilience assessment enables bridges to maintain their structural integrity and functionality in the face of loads and disasters, improves their reliability and recovery capability, and ensures the smooth flow of transportation. This study focuses on the assessment methods and indicator selection for the seismic resilience of bridges, summarizing the latest research progress in this field. It reviews the development history of commonly used bridge resilience assessment methods and frequently used assessment methods, and comparatively analyzes the advantages and disadvantages of experimental research and numerical simulation. Several bridge resilience assessment frameworks and evaluation models are introduced, including those for single bridges as well as for entire bridge networks, to assist researchers in selecting appropriate models and frameworks based on actual conditions. The key indicators for the seismic resilience assessment of bridges are reviewed, including structural strength, deformation capacity, durability, and reparability. Finally, future directions for research are proposed. The research indicates that assessment methods for bridge resilience under the coupled effects of multiple hazards are not yet mature and require further investigation. The close integration of intelligent algorithms with bridge resilience assessment is an important future research direction. This review aims to further promote the research and application of seismic resilience assessment for bridges.

Operating status prediction method for gas storage compressors based on BiLSTM

Chen, Hua — 2026-05-16T00:00:00Z

Journal of Vibroengineering, (in Press).
Hua Chen, Liang Wang, Shuang Li, Xiaohan Wei
Compressors serve as fundamental power units in underground natural gas storage facilities and frequently need to accommodate wide-range operational condition adjustments. However, their inherent nonlinear characteristics, coupled with high-noise and uncertain operating environments, pose significant challenges to precise control and safe operation. To accurately predict compressor operational status and provide reliable decision-making information for operation and maintenance, this study proposes an operating-state prediction method for gas storage compressors based on vibration-sequence analysis and a Bidirectional Long Short-Term Memory (BiLSTM) network. Singular Spectrum Analysis (SSA) is first applied to decompose and reconstruct monitoring signals, extracting dominant trend components while suppressing background noise. A Convolutional Neural Network (CNN) is subsequently employed to capture multi-scale local features, after which the BiLSTM network learns temporal evolution patterns from the extracted features. The Adam optimizer is utilized to enhance training stability and prediction accuracy. Experimental validation using real monitoring data from gas storage compressors indicates that the proposed method achieves precise and reliable prediction of compressor operating states.

Structure reconstruction of anchor winch drum based on parameterized surrogate model with lightweight design

Zhou, Guangqian — 2026-05-25T00:00:00Z

Journal of Vibroengineering, (in Press).
Guangqian Zhou, Lihong Guo, Xuehong Huang
To improve the operational stability of the anchor winch, parametric reconstruction of the winch drum structure was conducted based on surrogate model technology. With the stress peak value and natural frequency as constraint conditions, lightweight design of the overall structure was implemented, effectively achieving energy conservation and consumption reduction. A parametric model coupling strength and modal characteristics of the winch drum was established using the finite element method. Taking the stress peak value, first-order natural frequency, and mass as objective functions, a response surface was fitted according to the mapping relationship with discretized parameter dimensions, and error verification was conducted. An optimization mathematical model of the winch drum was constructed, and the sequential quadratic programming (SQP) algorithm was adopted to solve the extremum of the model under different constraint conditions. Research indicates that the proxy model exhibits high accuracy. Under conditions of 1 time and 1.5 times the peak stress, the weight of the anchor drum can be reduced by 17.4 % and 27.6 %, respectively, with the natural frequencies remaining no lower than the initial values. The research method can significantly improve the cost-effectiveness of mechanical design and achieve good energy-saving and consumption reducing effects.

Gearbox compound fault diagnosis using CEEMDAN feature extraction and a dual-attention multi-scale BiLSTM model

Wu, Lianxin — 2026-05-25T00:00:00Z

Journal of Vibroengineering, (in Press).
Lianxin Wu, Xiaojie Sun
As a core component of mechanical transmission systems, the gearbox's operating state directly determines equipment reliability and industrial production safety. In actual working conditions, a single fault can easily evolve into a complex fault mode with multiple coupled faults. Traditional diagnostic methods face challenges such as insufficient feature extraction and low fault mode discrimination. To address this issue, an intelligent diagnostic model is proposed that integrates adaptive noise complete set empirical mode decomposition (CEEMDAN) feature extraction, multi-scale convolution, and a dual attention mechanism. First, CEEMDAN is used to decompose the vibration signal at multiple scales. After effective IMF filtering, time-domain, frequency-domain, fault-specific, and coupled interactive features are extracted to form a multi-dimensional feature set. Then, adaptive principal component analysis (PCA) is used to reduce the dimensionality to obtain a low-redundancy feature set. Subsequently, a diagnostic model containing multi-scale convolution, a bidirectional long short-term memory network (BiLSTM), and dual attention branches is constructed, and an improved loss function is combined to enhance the ability to distinguish complex fault features. Experimental results based on the Beijing Jiaotong University bogie gearbox bench dataset verify the effectiveness and robustness of the proposed method under complex fault modes, providing a reliable technical solution for gearbox fault diagnosis in industrial scenarios.

Dynamic modeling and screening performance of a double-layer forced synchronous circular vibrating screen

Li, Hongxi — 2026-05-28T00:00:00Z

Journal of Vibroengineering, (in Press).
Hongxi Li, Enhui Zhou, Haishen Jiang, Ling Shen, Zixin Yin
The double-layer forced synchronous circular vibrating screen (DLFSCVS) is one of the most effective solutions for material screening. In this paper, a dynamic model was established to control the vibration of the screen, and the vibration characteristics of DLFSCVS are obtained by vibration experiment and parameter analysis. The classification performance of DLFSCVS was studied by EDEM, and the screening mechanism of DLFSCVS was revealed. The results show that the established dynamic model can describe the vibration of DLFSCVS well, and the maximum deviation between the experimental results and the theoretical results was within 4.78 %. The trajectory of the screen box is approximately circular. When the vibration frequency is 14 Hz, the acceleration amplitude of the screen box in the X and Y axis directions is 34.7 and 35.2 m/s2, respectively. With the increase of vibration frequency, the displacement amplitude of the screen box is basically unchanged, and the velocity and acceleration amplitude increase gradually. The results showed that when f= 14 Hz, the screening efficiency of the upper and lower screen plates up to 0.87 and 0.93, respectively.