The excitation source in actual engineering is relatively complicated, which often presents non-Gaussian features.As a result, the assumption of Gaussian process is no longer applicable.Therefore, it is necessary to carry out the simulation of non-Gaussian process.Currently, the usual method is to realize the simulation of non-Gaussian process through the translation of Gaussian process.Compared with the common implicit mapping, Hermite polynomial model (HPM) and Johnson translation model (JTM) provide more efficiently the explicit translation between the non-Gaussian process and standard Gaussian counterpart.How to further improve the simulation efficiency against the HPM-HTM hybrid model was investigated.Firstly, in order to avoid the iterative process, the parameter estimation process of HPM and JTM was optimized based on the support vector regression to improve the efficiency of parameter estimation.Subsequently, through the comparison of the simulation flows based on the linear filtering method and harmony superposition method, the simulation efficiency was improved in the non-Gaussian process simulation.Finally, the examplic analysis results of the wave field and fluctuating wind field were combined presented to demonstrate the accuracy and efficiency of the modified simulation process.The results show that the improved simulation flow can realize the high-efficiency simulation of the multivariate non-Gaussian process with the guarantee of accuracy.

With the growth of the global demand for renewable energy, various types of semi-submersible floating wind turbines have been emerging, and the impact of the marine environment on their dynamic responses has also attracted wide attention.The generation of rogue waves was investigated and rogue waves aligning with actual sea conditions were simulated.Based on this, the analysis focused on the platform dynamic responses of a novel semi-submersible wind turbine, considering the coupling between the floating wind power devices and aquaculture nets, under the influences of rogue waves, such as the longitudinal sway, lateral sway, pitch, and acceleration.Additionally, the dynamic responses of the wind turbine components, such as cabin acceleration, tower top load, and output power, as well as the dynamic responses of the mooring anchor chain (effective tension), were examined.The research findings indicate that rogue waves have a negligible impact on the average values of various response parameters but significantly affect their extreme values and standard deviations.Specifically, the influence of rogue waves causes the longitudinal sway response of the semi-submersible platform to exhibit impulsive characteristics, which has critical implications on the output power and stable operation of the wind turbine.During the occurrence of rogue waves, a significant dip in output power is observed.Moreover, the effective tension of the anchor chain also displays impulsive responses, and due to the catenary effect, the rate of increase in tension under the influence of rogue waves is found to be less than the rate of decrease in tension.Based on this research, the complex effects of rogue waves on the semi-submersible wind turbine system have been revealed.In addition, it provides valuable reference data for future studies in related fields.

To effectively solve the problem of low monitoring accuracy that occurs in the visual-based monitoring method, a wind turbine characteristic identification method based on the deep learning motion amplification technology combined with the visual monitoring method was proposed.Firstly, the encoder, operator and decoder were used to construct a deep learning network framework for motion amplification, to realize the generation of arbitrary amplification rate of motion information in the video.Second, the Lucas Kanade optical flow method combined with the Shi-Tomasi corner detection was utilized to enhance the visual robust monitoring capability of the magnified video.Finally, a wind turbine model was used for experimental validation, and the experimental results show that the deep learning-based motion amplification technique combined with visual monitoring can effectively recognize the wind turbine power characteristics under different environment of the wind turbine, and the accuracy can be as high as 98% or more.Through the combination of the motion amplification technology and visual monitoring method, small vibration, long-distance, non-contact and low-cost structural health monitoring can be realized, which provides a basis for the state assessment of large-scale structures such as wind turbines and other heavy industrial installations.

In heavy icing aera, multi-bundle conductors may experience a phenomenon where multiple sub-conductors become bonded together by ice, forming a single unit. This severe icing significantly increases the wind-exposed area of the conductor and deteriorates its aerodynamic profile. Consequently, the integral ice-covered state of multi-bundle conductors may result in a more pronounced wind-induced swing during the ice shedding process. This paper conducts wind tunnel tests on the aerodynamic characteristics of heavily iced transmission lines with two types of icing: integral ice-covered and independently ice-covered sub-conductors. Using the nonlinear finite element method, the dynamic responses of heavily iced twin-bundle conductors under joint action of ice-shedding and wind was simulated. The numerical simulation comprehensively considers the coupling effects of wind loads in the along-wind and vertical wind directions, the significant aerodynamic damping effect caused by fluid-structure interaction, and the abrupt change in wind load due to the alteration in aerodynamic shape and coefficients at the moment of ice shedding. The study analyzes the influence of icing types, wind attack angles, and wind speeds on the unbalanced tension, jump height, and axial force of insulator strings following conductor ice shedding. A simplified formula for calculating the maximum unbalanced tension is proposed. The results indicate that the maximum unbalanced tension during the ice-shedding process of heavily iced twin-bundle conductors is approximately 1.65 times the static unbalanced tension of ice accretion. Wind action may increase the maximum unbalanced tension and jump height of heavily iced twin-bundle conductors following ice shedding by approximately 29% and 16%, respectively, while its impact on the axial force can be neglected. This study provides a reference for the design of transmission lines in heavy icing aeras and for revisions to current standards.

To investigate the dynamic response of subconductors during asynchronous de-icing, finite element models were developed for twin, quad, and hex-bundled conductors with spacer systems. A method for calculating the deflection angle of the spacers was proposed. Furthermore, this study examined the system response under partial-position de-icing and zipped de-icing of twin-bundle conductors, and identified the most adverse de-icing combinations for quad and hex-bundle conductors. It analyzed the de-icing response results, such as conductor jump height, horizontal stress, and spacer bar deflection angles, and studied the influencing factors of conductor torsion. The research findings indicate that the jump height of the de-iced sub-conductor is greater than that of the other sub-conductors, yet it experiences less horizontal stress. The maximum jump height occurs at the sub-span conductor located at the center of the span. For twin-bundle conductors, the risk is minimized when both sub-conductors de-ice synchronously from one end to the other. However, there is greater risk if the ice at the center of the span falls off first. For multi-bundle conductors, it is crucial to avoid scenarios where only the lower conductors are de-iced while the upper conductors remain heavily iced, as this combination can easily lead to spacer flipping. Priority should be given to synchronously de-icing the upper pair of sub-conductors during de-icing operations. 

A novel honeycomb sandwich structure is designed. The structure combines an ortho-hexagonal honeycomb sandwich's high static load-bearing capacity and lightweight properties with an Archimedean spiral resonator system integrated inside the sandwich structure. This embedded sandwich panel uses helical resonators to achieve ultra-low effective dynamic stiffness, and its designed lattice constant can be two orders of magnitude smaller than the wavelength of the bandgap. Using an equivalent of the resonator as a spring-mass system, the theoretical computational model shows that the location of the bandgap is determined by the natural frequency of the resonator, while the bandgap width is affected by the mass ratio of the resonator to the main structure, and the validity of the model is verified using finite element methods. The numerical simulation results indicate that the structure has good bandgap tunability. Finally, an integrally molded prototype is fabricated using 3D printing technology, and laser scanning vibration measurement experiments are completed, which show that this honeycomb sandwich metamaterial plate has an average vibration suppression effect of 21 dB in the designed bandgap range.

The contact stiffness has an important influence on the intrinsic properties of the structure. In order to accurately establish the dynamic model of the contact surface between the spiral bevel gear and the connector, the modal frequencies and modal vibration shapes of the gear and connector assembly were extracted through modal experiments. A finite element model of the gear and connector assembly is established, the distribution law of contact pressure with different preload is analyzed, the contact main region and contact subregion are divided, and 3-way equivalent stiffness spring units are established respectively. Comparison with the experimental results shows that the stiffness of the contact main region and the contact subregion have a great influence on the modal frequency of the structure as a whole. The spring stiffnesses were analyzed for modal frequency sensitivity, and the main spring stiffnesses affecting the modal frequency of the structure were identified. With the experimental modal frequency as the target to correct the main spring stiffness, the maximum relative error of the corrected modal frequency is reduced from 4.25% to 1.83%, which significantly improves the accuracy of the model. The research method lays a foundation for accurate dynamic characteristic analysis of spiral bevel gear and further structural optimization and vibration reduction.

Centrifugal pump stalls not only reduce the pump performance but also easily cause surges, seriously affecting the stability of centrifugal pumps.   The researches on centrifugal pump stalls are reviewed, and three common stalls of the rotational stall, fixed stall, and alternating stalls that occur in centrifugal pumps are summarized. It also elaborates on the characteristics, manifestations, and impact on the pump performance of each stall type. For the study of centrifugal pump stalls, a combination of experimental and computational fluid dynamics methods is often used. The experimental research mainly adopts particle image velocimetry technology, and the pressure measurement on the shroud in compressors can also be referenced for open centrifugal impellers. Moreover, the analysis methods including wavelet analysis, digtial micromirror devices, POD, and cross-power spectrum can be employed to provide a more comprehensive understanding of stall in fluid machinery. The stall mechanism of centrifugal pumps can be attributed to two main factors: the geometric structure of centrifugal pumps and complex operating conditions. Regarding the flow characteristics of stall, two main measures of compensation and suction method can be taken to inhibit stall.

The deformation of helical gear tooth will make the paired gears enter into meshing in advance or secede laggingly, where the meshing point of gear deviates from the theoretical position to produce the impact of approach or recess. The impact phenomenon of entering or exiting meshing in helical gear transmission can be reduced or avoided by using the modified tooth profiles. In this paper, a calculation model for gear meshing stiffness, length of tooth contact line and load distribution coefficient was established based on the mechanism of gear contact and the slice method, considering the contact stiffness of tooth surface and the extended meshing phenomenon caused by tooth bending deformation. The proposed method in this paper is used to study the meshing stiffness and fluctuation characteristics of helical gear under different modification parameters and external loads. Compared with the results in the literature, it is shown that the proposed method can calculate the meshing stiffness of helical gear more efficiently and accurately, and obtain the internal relationship between the meshing stiffness fluctuation coefficient and the tooth tip modification parameters and the transferred load.

As a flexible bridge, the deflection control of the main girder is particularly important during the operation of a suspension bridge. To predict the vertical deflection of the main girder of an existing suspension bridge under the combined effects of random traffic flow and environmental temperature, this paper establishes an integrated deflection interval prediction method based on Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, probability density estimation layer, and bridge monitoring data. Using health monitoring data from the Nanxi Yangtze River Bridge, a time series training set of environmental temperature, vehicle load, and deflection monitoring data was established. The combined CNN-LSTM layers captured local features and long-term memory in the time series. A Gaussian distribution was used as the probability density function, and the parameters of the Gaussian distribution were evaluated using the maximum likelihood method, resulting in optimal deflection prediction values and probability intervals. Based on this, a method for identifying abnormal deflection and warning thresholds for the main girder of existing suspension bridges was proposed. The study shows that compared to LSTM and CNN-LSTM models, the CNN-LSTM-GD model has better predictive capabilities for small deflection fluctuations and extreme deflections, with deflection prediction values closely matching the monitoring data. Over a 24-hour time scale, compared to the traditional LSTM model, the CNN-LSTM-GD model improved the Root Mean Square Error (RMSE) and the coefficient of determination (R2) by 54.40% and 10.22%, respectively. Compared to the CNN-LSTM model, the improvements in RMSE and R2 were 38.43% and 5.31%, respectively.

The stochastic resonance of a dielectric elastomer bistable system under the combined effect of Gaussian white noise and harmonic excitation is investigated. First, considering the unavoidable random factors that always exist in practical engineering and applications, a dielectric elastomer model under Gaussian white noise excitation is established and the parameter conditions satisfying the bistable case of the system are given. Secondly, the Fokker-Planck equation for the total energy is derived using the energy envelope stochastic averaging method, based on which its steady-state probability density and the joint probability density function are obtained. Then, the analytical expression for the system's signal-to-noise ratio is deduced based on the most rapid descent method and two-state model theory. Finally, the effects of parameters such as Gaussian white noise and holding part mass on the stochastic resonance of the dielectric elastomer bistable system are discussed in detail and verified numerically with the help of the statistical complexity method. The results show that the non-monotonic structure of the signal-to-noise ratio curve implies that the system generates a stochastic resonance phenomenon; a larger holding part mass coefficient suppresses the generation of stochastic resonance, while the moving part mass coefficient enhances the stochastic resonance behavior. In addition, the evolution trend of the statistical complexity curve is consistent with that of the signal-to-noise ratio curve.

In order to explore the dynamic process of self-excited pulsed fluid jets in annulus breaking coal and rock, the smoothed particle hydrodynamics-finite element method algorithm was used to establish a numerical calculation model of self-excited pulsed fluid jets impacting coal and rock under submerged conditions. The accuracy of the model was verified through theoretical analysis and experimental comparison. The effects of confining pressure, pump pressure and jet type on rock-breaking efficiency were discussed, and the damage mechanism and stress propagation laws during erosion of coal and rock were studied. The results show that under different confining pressures, the erosion depth of the self-priming pulsed jet is significantly increased compared with the self-excited pulsed jet and the ordinary jet, indicating that the self-priming pulsed jet can better break the water cushion effect to a certain extent. When the confining pressure increases from 0MPa to 0.4 MPa, the depth and volume of the erosion pits of self-priming pulsed jet decrease linearly. The depth of the erosion pits decreases by 36.36%, and the volume of the erosion pits decreases by 17.18%. The depth and volume of the erosion pits increase linearly with the increase of pump pressure. In the range of 2 to 8MPa, the depth of the erosion pits increases by 650% and the volume of the erosion pits increases by 847.86%. In the range of 8 to 12MPa, the depth of the erosion pits increases by 23.33% and the volume of the erosion pits increases by 41.92%. Through the laws of coal and rock damage and stress propagation during the erosion process, it is found that along the radial direction, from the center of coal and rock impact to the distal end, the degree of damage and effective stress gradually decreases and tends to be stable, with a certain limit range; along the axial direction, the rapid accumulation of damage and effective stress at the measuring points reaches the peak one after another, and the coal and rock units quickly accumulate to complete damage, forming erosion pits.

In this paper, a theoretical model on plastic dynamic response of foam-core sandwich plate subjected to rectangular mass impact loading is established based on the rigid-perfectly plastic material assumption and the power conservation principle. Numerical simulation of PVC foam core sandwich plate under rectangular mass impact was carried out to verify the accuracy of the theoretical model. In addition, the influences of impactor width and foam core thickness on the impact response of foam core sandwich plate are theoretically analyzed. Results shows that the theoretical prediction results on plastic dynamic response of foam-core sandwich plate subjected to rectangular mass impact show good agreements with numerical results. The increase of loading concentration results in severer plastic deformation, the increase of foam core thickness can improve the impact resistance of foam core sandwich structures.

The cushioning foam structure protection measures exhibit excellent protective effects. To investigate the energy dissipation effect and impact resistance mechanism of the reinforced concrete (RC) columns designed for protection during collisions，This paper is based on the pendulum impact test data, numerical simulations are conducted using LS-DYNA to analyze the dynamic response and failure modes of reinforced concrete (RC) columns under impact loading, and the effectiveness of the numerical model is validated. The study investigates the impact resistance of RC columns with three different protective measures: unprotected, polyurethane (PU) foam protection, and a composite protection using wire mesh and mortar. The results indicate that both protective measures significantly enhance the impact performance of the RC columns. Under pendulum impact loading, the wire mesh-mortar composite with PU foam demonstrates excellent impact resistance. Specifically, compared to PU foam protection alone, incorporating wire mesh with composite mortar on the outer layer of PU foam reduces the peak impact force and displacement by approximately 20% and 25%, respectively, at the same protective thickness. The columns  demonstrate enhanced impact resistance at various impact velocities, and increasing the thickness and density of the cushioning layer effectively improves the impact resistance of the RC columns.

The impact damage accumulation model plays a crucial role in the impact resistance design and life prediction of materials. In order to accurately quantify its evolution process and probability characteristics, a damage model and average life prediction formula based on the principle of equivalent failure probability are proposed. Firstly, the general distribution characteristics of material fatigue life and damage accumulation, as well as the general laws of impact fatigue damage accumulation, are analyzed. Secondly, based on the equivalent theory of failure probability, the corresponding probabilistic damage model and expected life formula are provided. Finally, taking 6061 aluminum alloy shaft as the experimental object, the prediction errors of the damage model based on the principle of equivalent failure probability and the cumulative damage mean model are compared. The results show that the former has significantly better prediction accuracy than the latter. The fatigue damage accumulation rate of aluminum alloy specimens is relatively high in the early stage, gradually decreases with the increase of loading times, and finally shows a rapid growth trend. It is proved that the proposed impact damage probability model is reliable, which provides theoretical reference and data basis for the study of probabilistic damage of materials.

In order to evaluate the effect of ground motion duration on residual displacement of reinforced concrete pier, an elastic-plastic spectrum model of single-mass single-degree of freedom (SMSDOF) system was constructed. The difference of residual displacement of SMSDOF system under short-duration unidirectional ground motions and long-duration unidirectional ground motions was compared and analyzed. A single-mass bi-degree of freedom (SMBDOF) system model was constructed based on the SMSDOF system model. The effects of stiffness ratio and lateral strength ratio on the residual displacement of SMBDOF system under short-duration bidirectional ground motions and long-duration bidirectional ground motions were investigated. The difference of residual displacement of SMSDOF system under short-duration bidirectional ground motions and long-duration bidirectional ground motions was compared and analyzed. The results show that the ratio of the residual displacement ratio of the SMSDOF system under long-duration and short-duration unidirectional ground motions is close to 1.5,,for lateral strength ratios greater than 4 in the medium- and long-period region. The effect of stiffness ratio on the residual displacement of SMBDOF systems under short-duration bidirectional ground motions is negligible. The effect of stiffness ratio on the residual displacement of SMBDOF systems under long-duration bidirectional ground motions is significant, and the residual displacement of SMBDOF systems under long-duration bidirectional ground motions increases with increasing stiffness ratio. Under the action of bidirectional long-duration and bidirectional short-duration ground motions, the ratio of the square and square root residual displacements of the SMBDOF system along two orthogonal directions reaches 1.9,for lateral strength ratio equal to 6 in the long-period region.

In response to the current lack of clarity regarding the seismic response characteristics and the influence of key parameters on floating bridges, a comprehensive finite element numerical model of the main beam, pier columns, pontoons, and anchor cables was established. To address the Fluid-structure interaction problem, the added mass method was employed to simulate the hydrodynamic inertial forces induced by seismic motion, while other hydrodynamic loads acting on the pontoons and anchor cables were modeled using the Morison equation. The dynamic response characteristics of the floating bridge system and the influence of key parameters were analyzed under various seismic motion characteristics, intensities, and directions. The results indicated that significant differences in the floating bridge response were observed depending on the characteristics of the seismic motion. Long-period seismic motions with low frequencies and concentrated energy generated larger responses in the floating bridge, whereas short-period seismic motions with high frequencies and dispersed energy induced relatively smaller responses. It was also found that when the system's dynamic response in the x-direction was analyzed, it excited a dynamic response in the z-direction. In other words, applying seismic motion only in the x-direction resulted in a dynamic response in the z-direction, causing a noticeable difference between the seismic responses in the z-direction and those in the x-y-z directions, with the latter being significantly larger. When the added mass was considered, both the acceleration and displacement responses of the floating bridge were found to be greater than in the case without added mass. Structural damping was observed to have a certain suppressive effect on the floating bridge’s response, while the impact of the drag forces on the pontoons and anchor cables on the system's response was relatively small.

The theoretical and applied research on the conditional mean spectra of ground motion in China has been developed, but the research on vertical conditional spectra considering the correlation between the horizontal and vertical spectral shape of Chinese ground motion was still relatively insufficient. Based on the above research background, the vertical conditional spectrum theory was first introduced in this paper; then Chinese site-related ground motion prediction model was generated based on Chinese ground motion data, the marginal distribution and joint distribution of horizontal and vertical spectral shape of Chinese ground motion were constructed based on the Copula function, and the conditional mean spectral model considering acceleration correlation between horizontal and vertical spectral shape of Chinese ground motion was proposed. Finally, an applied case study was performed to generate horizontal and vertical conditional spectra for a nuclear power plant site in South China, and the joint horizontal and vertical ground motion records were selected based on the horizontal and vertical conditional spectra.The research results show that the horizontal and vertical spectral shape of Chinese ground motion can follow the bivariate normal distribution; the vertical conditional spectra theory proposed in this paper considering the correlation between the horizontal and vertical spectral shape of Chinese ground motion would generate the relevant vertical conditional spectra of the site in China, and could provide the matching target basis for the joint selection of horizontal and vertical ground motion of the site in China, and could provide the basis of vertical seismic fortification for high-rise structures, large-span bridge structures, and seismic isolation structures in high-intensity zones. 

The two ends of submerged floating tunnel (SFT) are the main excitation points for earthquakes. To study the dynamic response of SFT under seismic loads, a tunnel-cable coupled vibration model with flexible constraints at both ends was established. A vibration mode function of the tunnel that conforms to flexible constraint conditions was constructed. The Galerkin method was used to obtain the system of coupled vibration ordinary differential equations in generalized coordinates, and a program was written in MATLAB to solve the equation. The correctness of the theoretical method was verified by comparing with the finite element results. Based on the example of a submerged floating tunnel to be constructed, the influence of boundary constraint parameters on structural response was explored. The results show that there is a significant deviation between the seismic response results of flexible constraints and those treated as simple hinged or fixed connections. The response of the tunnel decreases as the stiffness of rotating spring at both ends decreases. Reducing the stiffness of linear spring can decrease the acceleration and bending moment response of the tunnel, but it will lead to an increase in displacement at tunnel ends. The excitation of the tunnel ends under earthquake has a significant impact on the response of the tunnel, accounting for over 75% and 85% of the vertical acceleration and bending moment responses.

Due to the frequency-dependent characteristics of viscoelastic damping mechanical systems, solving their eigenvalues is highly challenging, especially for large-scale mechanical systems characterized by multiple damping models. In this paper, a mechanical system with multiple damping models is taken as the research object, and an eigenvalue dimension reduction method based on physical subspace is proposed, which achieves highly precise and efficient prediction of modal frequencies and vibration shapes. Firstly, multiple damping models are transformed into a unified rational fraction form, constructing a general damping system with a consistent and concise form. Next, utilizing the unified form, a physical space with the same dimension as the system is constructed, enabling the recursive generation of the physical subspace. By combining the state space with the Krylov subspace to derive the physical subspace, a dimension reduction method for eigenvalue solving based on the physical subspace is proposed, effectively addressing the issue of dimensionality explosion in traditional state-space representations for systems with multiple damping models. Theoretical and numerical analyses demonstrate that the proposed method offers superior efficiency and accuracy compared to conventional state-space-based dimension reduction approaches.

In order to achieve lightweight design of the spacers installation robot to reduce the difficulty of rising to the wires, finite element analysis of frame under various typical working conditions was conducted. Based on the analyzed working condition data and experience, a directional weight allocation scheme was obtained using the analytic hierarchy process. Using the linear weighted method, taking the weighted flexibility minimum as the goal function under the multi-working conditions, the continuous topology optimization of the frame is realized. The frame was redesigned based on the final topology result. The results showed the maximum stress of new frame under three working conditions are reduced by 1.6% , 5.1% , and 3.7% respectively, the maximum displacement are increased by 6.5 %, 15.9 %, and 18.3 % respectively. The mass decreased from 16.582 kg to 11.099 kg, a decrease of 34.7%.

Manual grinding during shipbuilding and maintenance is characterized by high complexity, low efficiency, and substantial risks, making it a significant bottleneck in the industry's modernization efforts. To address these challenges, a Cable-Driven Parallel Grinding Robot (CDPGR) has been developed. A dynamic model of the CDPGR, incorporating ship motion as an external disturbance alongside the reaction forces generated during grinding, is established using the Lagrange method. To enhance the system's robustness against disturbances and improve control precision beyond the capabilities of existing controllers, a Second-Order Integral Terminal Adaptive Sliding Mode Controller (SOITASMC) is proposed based on the dynamic model. The control system's stability is rigorously validated through Lyapunov theory. Simulations under complex operating conditions demonstrate the effectiveness of the SOITASMC, with comparative analyses highlighting its advantages over traditional controllers. A scaled prototype of the CDPGR is subsequently constructed, and experimental evaluations are performed. Results show that, compared to existing controllers, the SOITASMC reduces steady-state position error by an average of 0.05 m, steady-state angular error by 1.09°, and rise time by 0.8 s. Additionally, binary image analysis of pre- and post-grinding steel plates indicates that surface smoothness improves from 22.34% to 69.51%. These findings affirm the superior performance of the SOITASMC and the practical effectiveness of the CDPGR for grinding tasks. This research provides valuable insights and innovative solutions for applying cable-driven parallel robots in shipbuilding and maintenance operations.

To suppress the structural vibration caused by external excitations during the service period of a space deployable cable-net antenna, an adaptive composite control method is proposed to accurately control the antenna structural vibration with high gain. First, a dynamic model of the cable-network antenna is established using multiple parallel active cables as actuators. Then, an adaptive composite controller is designed by integrating proportional-integral-differential(PID) control and Filtered-x Least Mean Square (FxLMS) control. High control gain is provided through multiple independent narrowband adaptive sub-controllers based on the main vibration frequency of the antenna structure., improving the problem of insufficient gain of PID control for frequency vibration control. Finally, simulation test verification research is carried out with the goal of active radial vibration control of antenna structures. Simulation and experimental results show that the adaptive composite control method has good control performance, and verify the efficient control ability of the adaptive composite control method to antenna structure vibration. The designed control method provides an effective technical means for active vibration control of antenna structures.

Based on the idea of active stiffness designing, the joints stiffness of typical air rudder effectors is analyzed, and a stiffness designing method of air rudder effector is proposed from the perspective of meeting dynamic characteristic(amplitude and phase) requirements. The accurate stiffness analyzing and designing of air rudder effectors can be achieved in the preliminary structural design stage. Firstly, the dynamic model and torsional stiffness model of air rudder systems are established, and the 9th-order transfer function model of the system is derived to obtain the frequency response function of the effectors. After that, the dynamic characteristic requirements is employed to limit the stiffness range that meets the amplitude-frequency and phase-frequency requirements of the system at each frequency point, and then, the stiffness of air rudder effectors can be accurately obtained by comprehensive considering stiffness at all frequency point. Thereby completing the design of the overall stiffness of the effectors. Finally, a SIMULINK nonlinear model is built to verify the proposed method, and the experiment results demonstrated that the method can realize accurately designing for an air rudder effector, which can confirm all stiffness range of the rudder effector that meet dynamic requirements.

At present, the influence of positioning node with frequency varying stiffness on vehicles mainly focuses on the curve passing performance, and rarely involves the influence on the hunting stability of bogies. This paper focuses on positioning nodes with frequency varying stiffness, the mechanism of the "frequency varying " was studied firstly, and then the transverse dynamics model of bogie with frequency variable stiffness node and traditional fixed stiffness node were established respectively, and the difference between the two nodes about the linear and nonlinear stability on the new and weared wheel were analyzed, finally, the influence of parameters of frequency varying stiffness node on system stability was studied, and the following conclusions were obtained: (1) With the increase of speed, the linear stability of bogie with frequency varying stiffness nodes increases first and then decreases, while the linear stability of bogie with traditional fixed stiffness nodes gradually decreases; (2) In the new wheel state, the stability of the frequency variable stiffness node is not as good as that of the traditional fixed stiffness node, especially the nonlinear stability; (3) In the state of wear wheel, the frequency varying stiffness node has more advantages in maintaining the linear stability of the hunting, but the nonlinear stability is lower than that under the traditional fixed stiffness node;(4)The parallel stiffness ks mainly affects the stability of the system at low speed, and the larger the ks, the higher the stability,the series stiffness kc mainly affects the stability of the system at high speed, and the smaller the kc, the higher the stability.

To explore the spatial and aerodynamic conditions for the development and application of lift wing technology in next-generation high-speed trains, optimize the aerodynamic shape, operational attitude, and crosswind resistance of lift wing profiles. A fusion design method for train lift wings and body under limit constraints is proposed, and numerical simulation technology is used to analyze the aerodynamic selection design, installation layout, aerodynamic characteristics and operating attitude of lift wings in strong crosswind environments. The results show that based on the current high-speed railway technology standard system in China, considering installation space redundancy, streamlined coordination of appearance, aerodynamic performance, and working scale, the selection of lift wings with a flat convex wing profile for roof layout has better comprehensive performance; The lift and drag coefficients of the lift wing approximately follow a parabolic relationship within the range of -30 ° to 30 ° angle of attack. The aerodynamic efficiency reaches its maximum when the angle of attack is about 16 °; The aerodynamic lift acting on the lift wing varies significantly with different longitudinal positions. Among them, when the longitudinal position of the lift wing is about 2 meters away from the streamlined tail end connection at the front end of the driver's cab of the head car, the contribution of lift is most prominent, and the proportion of aerodynamic lift generated by the head car is the highest at 61%; Under strong crosswinds, the aerodynamic forces and moments acting on high-speed trains with lift wings exhibit varying degrees of sinusoidal fluctuations with the variation of wind direction angle. The aerodynamic lift performance is most prominent in crosswind conditions; When the horizontal rotation angles of the lift wing are about 120 ° and 300 °, the comprehensive aerodynamic performance and efficiency are optimal. The optimal matching working posture of the lift wing under crosswind provides important technical reference for ensuring driving safety, and has a significant improvement effect on balancing and compensating the aerodynamic characteristics of high-speed trains in crosswind environments.

An efficient and accurate method for assessing the vibration source intensity (VSI) induced by metro trains was proposed. Based on periodicity theory, the fundamental solutions for each part were obtained. The analytical solutions for calculating VSI were developed in the frequency-wavenumber domain by considering displacement compatibility, stress equilibrium, and the expressions for train loads. The influence of train speed, track irregularities, and soil parameters on VSI was investigated, and the accuracy was confirmed through comparisons with the measured VSI. Results show that when wavenumber M=8 is applied, the predicted results converge and the prediction error is 0.7 dB .VSI rises with an increase in train speed, a decline in track condition, and a reduction in soil modulus. VSI increases by 15 dB as the track irregularities degrade from American class 6 to class 1. The track irregularities should be considered in environmental assessments. This method takes approximately 58 seconds per prediction, making it suitable for determining VSI in environmental assessments due to its high efficiency and accuracy.

To address system instability and error accumulation caused by multi-point chord measurements, a spatial calculation method based on area parameters is proposed for waveform reconstruction. This method reduces errors caused by matrix singularity by transforming high-dimensional matrix into one-dimensional vectors. Using multiple harmonic waves as short-wave irregularity for simulation, the proposed approach achieves a correlation coefficient of 0.9914 for the area reconstruction waveform after applying area parameter calculations and the Levenberg-Marquardt(LM) optimization algorithm, with the error controlled within 5 ; Through optimization of measurement point configurations, the area parameter reconstruction model is compared with the chord value reconstruction model under identical configurations. Results show that the area parameter reconstruction model outperforms computational efficiency, reconstruction accuracy, and suppression of error accumulation. Experimental results on corrugation indicate that this method, when implemented on a detection trolley, accurately calculates corrugation amplitude with a repeatability accuracy of 10.42 . Furthermore, the identified wavelength peaks fall within the short-wave range, enabling precise measurement of rail short-wave irregularities.

Trapezoidal bolt connections serve as the primary joining method for equipment compartment skirts, base plates, and other components in high-speed railway (HSR) trainsets. However, during service, these bolts are subjected to prolonged exposure to severe vibration loads and alternating high and low temperature environments, leading to easy loosening and potential fatigue fractures. This poses risks and challenges to the reliable operation of HSR trains. To address this issue, an accurate finite element model of trapezoidal bolt connections has been established to simulate lateral, longitudinal, bending, and torsional vibrations, as well as alternating temperature loads. This model analyzes the loosening behavior of trapezoidal bolts under the individual and combined effects of these vibrations and alternating temperature loads. Furthermore, it systematically investigates the influence of initial preload, friction coefficient, and material of the clamped components on bolt loosening under lateral vibration conditions. The research findings indicate that lateral vibration is the primary load form causing trapezoidal bolt loosening, bending vibration can only lead to bolt loosening in specific circumstances, while longitudinal vibration, torsional vibration, and alternating temperature loads hardly cause loosening. Furthermore, the effects of vibration and alternating temperature loads are independent of each other. Moreover, the effects of vibration and alternating temperature loads are independent of each other. Compared to ordinary thread and pipe thread structures, trapezoidal bolt connections exhibit slightly inferior locking performance but demonstrate a 30% reduction in stress concentration under the same conditions. This will significantly enhance the load-bearing capacity and fatigue resistance of trapezoidal bolt connections. 

Accurately obtaining pavement unevenness information is crucial for intelligent suspension control, which directly affects vehicle dynamics and comfort. Therefore, this paper aims to improve the accuracy of pavement unevenness estimation, based on the 4-degree-of-freedom model, take the body vertical vibration, pitch vibration and unsprung vibration information as the observation quantities, use the Kalman filter algorithm to build the pavement unevenness estimation observer, meanwhile, construct the particle swarm-support vector machine model using the body vertical acceleration information to realize the pavement class classification, and based on the pavement class design, put forward an adaptive updating algorithm based on the process noise covariance matrix, taking into consideration the process noise information. Adaptive updating algorithm is designed based on pavement class, and the pavement process noise adaptive pavement unevenness estimation algorithm is proposed considering the unsprung information. The simulation results show that the proposed algorithm can improve the real-time pavement unevenness estimation accuracy compared with the conventional augmented Kalman filtering algorithm under random pavement and impact pavement. 

Due to significant differences in data distribution and features of bearing life state under different devices caused by variations in structural dimensions, operating conditions, and other factors, the accuracy of bearing life state recognition is often affected. To address this, an improved deep subdomain adaptive network (IDSAN) is proposed for cross-device bearing life state recognition.First, we introduce a channel attention mechanism in Resnet-50 to enhance the weights of important features in each channel, adaptively obtaining distributed feature representations of rolling bearings from different devices. Second, a Transformer encoder and a multi-scale convolution module are integrated into the network. The Transformer’s self-attention mechanism captures global information, while the multi-scale convolution module extracts multi-scale features, adaptively learning bearing life state characteristics across devices from multiple perspectives. Finally, subdomain adaptation is achieved using the Local Maximum Mean Discrepancy (LMMD) metric, ensuring effective domain alignment. Experimental validation on various bearing life datasets shows that the proposed method outperforms existing domain adaptation approaches in recognition accuracy, confirming its feasibility and effectiveness.

Aiming at the problem that the feature distributions of two domains of rolling bearings under the conditions of variable operating conditions have large differences, and the scarcity of target domain labels leads to low fault diagnosis accuracy, an unsupervised rolling bearing fault diagnosis method based on the joint structure of multi-source domains to maintain the migration is proposed. Firstly, the source domain with higher similarity to the target domain is screened out from the multi-source domain by the maximum mean difference metric; then the source and target domain data are projected to the common subspace by two projection matrices respectively, and the source and target domain samples are weighted, which maintains the neighboring relationship of the samples; at the same time, the marginal and conditional distributions between the two domains are aligned by using the maximum mean difference, and combined with the graph embedding theory and the Fisher's criterion Mining the shared potential fault structure features, and retaining the local flow structure and discriminative information of the data to minimize the domain differences; finally, using label propagation to obtain the predicted labels and judging the fault types through the voting mechanism. Experimental validation is carried out on four sets of rolling bearing datasets, and the proposed method outperforms the traditional method with good generalization performance.

Aiming at the problem that there are significant differences in the distribution of remaining useful life (RUL) degradation data of bearings based on unsupervised transfer learning, which leads to low prediction accuracy of the model, a joint domain adaptation bearing RUL prediction method is proposed to generate high-quality pseudo-labels to improve the RUL prediction accuracy.  Firstly, the efficient channel attention network (ECA-Net) and convolutional neural network (CNN) are fused to improve the feature extraction ability of the model.  Then, the Maximum mean square difference (MMSD) measurement method is used to reduce the distribution difference of degradation data between the source domain and the target domain, and high-quality pseudo-labels are generated. At the same time, the difference between the real labels in the source domain and the high-quality pseudo-labels in the target domain is compared, and weights are assigned to the samples to guide the model adversarial training and further improve the performance of the model.  Finally, in order to verify the effectiveness and superiority of the proposed method, it is compared with other methods on the IEEE PHM Challenger 2012 bearing dataset. Experimental results show that the proposed method generates high-quality pseudo-labels and has better prediction accuracy.

In structural health monitoring (SHM), reconstructing missing response data is crucial for accurately assessing the operational condition of structures. This paper proposes a missing vibration response reconstruction network based on Bidirectional Long Short-Term Memory (BiLSTM) and attention mechanism—Seq-BiAtt. Built on the sequence-to-sequence (Seq2Seq) architecture, this network models the response reconstruction problem as a sequence generation task, leveraging the potential spatiotemporal relationships within the data to significantly enhance the model's reconstruction performance. Additionally, a mean smoothing-based loss calculation method is proposed to evaluate the overall performance of the model. The robustness and accuracy of the proposed method are validated through numerical examples of an eight-degree-of-freedom vibration system and actual monitoring data from the Dowling Hall footbridge. Experimental results demonstrate that the model is capable of handling response reconstruction tasks in various noise environments, exhibiting excellent reconstruction performance even under low signal-to-noise ratio conditions.