Flexible cable supported photovoltaic are prone to be significant wind induced vibrations, which can lead to various structural safety and usability issues. Currently, the law of wind induced vibrations is not clear, and there are no corresponding vibration suppression measures. This study conducted wind tunnel tests on the full aeroelastic model of flexible cable supported photovoltaic. It synchronously measured the displacement and cable force of single-layer flexible cable supported photovoltaic, analyzed the effects of wind speed, inclination angle, and wind direction angle on displacement and cable force, proposed corresponding vibration suppression measures, and verified their vibration suppression effect through experiments. The results show that the flexible cable supported photovoltaic undergoes vertical and torsional coupled vibration under strong wind. The maximum displacement response occurs at wind suction and the maximum of cable force occurs under wind pressure. Therefore, wind suction is an unfavorable working condition for designing the joints. Meanwhile, wind pressure is an unfavorable working condition for designing columns and bases. The anchor cable has a significant mitigation effect on the vertical and torsional displacement at wind suction. The larger of the tilt angle is, the better mitigation effects. For the cable end force, the anchor cable can effectively reduce the fluctuation of cable force. The larger the tilt angle is, the more effective the cable force reduction.

Based on the basic concept of the generalized response displacement method, a dynamic sub-structure analysis method suitable for the longitudinal seismic response of a shield tunnel crossing longitudinally uneven sites is proposed. An explicit parallel calculation model of the longitudinal uneven free field and a three-dimensional (3D) refined explicit parallel calculation model of the surrounding rock-shield tunnel system are established by using the newly proposed sub-structure analysis method. The real-time transmission of dynamic deformation between the two models on the boundary is achieved through the sub-structure method. The free-field seismic wave at the buried depth of the tunnel is transformed into the equivalent earthquake action of the surrounding rock-shield tunnel sub-structure model. Compared with the traditional beam-spring model, the model method in this paper can achieve the 3D refined simulation of the surrounding rock-tunnel system and the longitudinal non-uniform ground motion input along the tunnel caused by the site seismic effect. The reliability of the model method in this paper is verified by comparing it with the calculation results of the 3D refined analysis model of the shield tunnel. The results show that the model method in this paper has a clear concept, simple modeling, low calculation cost and small differences in results, which can fully reflect the longitudinal seismic response of shield tunnel crossing longitudinal uneven sites. It provides a more efficient analysis method for the longitudinal seismic design of shield tunnels crossing longitudinal uneven sites with soft-hard connected media.

Aiming at the difficulties that the vibration response signal of the viscoelastic sandwich structure is strongly non-stationary and the change of vibration response signal caused by the change of aging state is weak, this paper proposes an intelligeat identification method for the aging state of the viscoelastic sandwich structure based on sparrow search algorithm (SSA) optimized variational mode decomposition (VMD) and adaptive neuro-fuzzy inference system (ANFIS）. The vibration response signals of different aging states of the viscoelastic sandwich structure are decomposed by the parameter-optimized VMD, and several intrinsic mode functions (IMFs) are obtained； The permutation entropy (PE) features of the obtained IMF components are computed, which are used to reflect the structural aging state change； The obtained permutation entropy features are constructed into feature vectors as inputs of ANFIS to realize the aging state intelligent iclentification of viscoelastic sandwich structure. The effectiveness of the method was verified through experiments, and compared with empirical mode decomposition (EMD) and ANFIS, parameter optimized VMD and radial basis function neural network (RBFNN) methods. The results show that the proposed method in this paper can more accurately identify the aging state of viscoelastic sandwich structure.

The flexibility of gear teeth under cyclic varying loads can induce meshing impact and nonlinear vibration of gear pairs. Revealing the multi-state meshing characteristics and nonlinear dynamic characteristics of spur gear systems considering teeth flexibility lays the foundation for the safe and reliable operation of transmission systems. Based on the cantilever beam theory and gear meshing principles, the flexible deformation of meshing teeth is calculated, and the calculation method for flexible time-varying meshing parameters of gear pairs is derived； based on the contact states and loading conditions of the gear pairs, extract the characteristics of multi-state flexible meshing, and a nonlinear dynamic model of the spur gear system with multi-status flexible meshing is established； study the evolution laws of flexible time-varying meshing parameters and the distribution characteristics of flexible deformation of gear teeth under multi-parameters correlation, and uncover the global bifurcation and chaos characteristics of the system when the teeth flank clearance changes. The results indicate that the flexibility of the gear teeth reduces the double teeth meshing area, affects the meshing parameters and multi-status meshing characteristics of the gear system, and induces out-of-line meshing of the gear pair； the variation of teeth flank clearance causes the coexistence of periodic motions and chaotic motions, and incomplete bifurcation under multiple initial conditions is the fundamental cause for such dynamic behavior coexistence.

To address the issue of unclear and challenging identification of non-contact rotating seal fault signals, this study established an experimental platform and acoustic emission testing system. It involved monitoring acoustic emission signals during various operational conditions, including normal operation and six typical fault scenarios of non-contact rotating seals. A total of 14000 feature samples were effectively collected. By applying the Bayesian optimization algorithm and incorporating continuous wavelet transform, an adaptive convolutional neural network classification model was constructed. Subsequently, the diagnostic performance of the fault recognition model was analyzed using confusion matrices and t-distributed stochastic neighbor embedding. The research results demonstrate that this model successfully classifies and identifies seven different operational conditions of non-contact rotating seals, including normal operation, dry friction, mixed lubrication, spring failure, end-face pitting, local spring failure, and end-face scratching, with an average recognition accuracy of 99.7023%. This achievement underscores the capability of effectively isolating and identifying seal fault sources from acoustic emission signals of non-contact rotating seals in non-stationary, complex, and overlapping environments, thereby establishing a solid theoretical foundation for practical engineering applications.

Blind source separation (BSS) can be used to extract modal coordinate vibrations from structural vibration signals. Complexity pursuit (CP) is one of the classical methods for solving the BSS problem. To improve the computational efficiency of the CP algorithm, this paper proposes two enhancements： it uses the negative log function of a Gaussian distribution as a nonlinear function to estimate signal complexity and derives formulas for rapidly computing signal complexity and its gradient； it employs a subspace search-based gradient descent algorithm to calculate the optimal mixing vector in the reduced subspace. The new formulas only require the covariance matrix of mixed signals and the covariance matrix of time delays when computing complexity and its gradient, without using all signal data. Numerical examples and structural vibration data are employed to evaluate the proposed method. The results demonstrate that the fast complexity pursuit algorithm outperforms traditional methods in terms of computational efficiency and accurately separates structural modal coordinate vibrations.

The uncertainty of the combined incidence angle of seismic waves often has a significant effect on the dynamic response of faced rockfill DAMS. In this paper, the motion field of surface control points is decomposed by the principle of wave field superposition, and the time history of incident P and SV waves is obtained by two‑dimensional inversion. The angle of incident P wave and SV wave in the wave input model are randomly selected by the method of number theory. The influence of the uncertainty of combined incident angle on the seismic response of asphalt concrete faced rockfill dam is studied by the dynamic calculation of different combined incident angles. Taking a practical project as an example, by analyzing the mean value, coefficient of variation, 95% confidence interval limit and extreme value difference of the horizontal peak acceleration of foundation surface, panel stress and acceleration, dam body horizontal peak acceleration and permanent deformation, and other statistical laws and distribution type tests, and compared with the vertical incidence of seismic waves, The influence of random combination incidence Angle and input ground motion intensity on random response dispersion degree and obedience probability distribution is analyzed. The results show that considering the uncertainty of the combined incidence angle, the seismic response dispersion of the foundation surface of the dam will increase. The maximum principal tensile stress of the panel increases by at least 40% compared with the calculated result of vertical incidence. The influence of the horizontal peak acceleration on the dam crest and the panel crest is greater than that on the permanent deformation. Compared with the results of vertical incidence, the permanent deformation of the three groups of seismic waves has a transcendental probability of more than 70%. The statistical results of seismic response of dam body may not accord with normal distribution. The dispersion of seismic response results of overlay layer is greater than that of dam body.

The wedge-shaped oil film in sliding bearings induces uneven heating effects on the journal of a rapidly rotating rotor, resulting in circumferential temperature variations in the journal. The thermal bending caused by these temperature differences exacerbates rotor vibration, leading to a phenomenon known as ‘Morton effect’ or rotor thermal instability. This effect is particularly severe in cantilevered rotors. Initially, an elliptical bearing’s thermal fluid lubrication model is established, and its dynamic coefficients and oil film temperature field are calculated. Subsequently, based on Fourier heat conduction theory, using the obtained oil film temperature as a boundary condition, a finite element method is employed to solve the three-dimensional transient temperature field of the journal to determine the thermal deformation and thermal stress. The thermal stress is then integrated to obtain an equivalent moment for rotor dynamic analysis. Additionally, the sliding bearing oil film thickness is updated based on thermal deformation. Repeating these steps completes the fluid-solid-thermal multi-field coupling analysis of the rotor-bearing system, and the effectiveness of the simulation model is validated against experimental data. Finally, parameter analysis is conducted on the rotor-bearing system with the rotor’s cantilever length and suspended mass as variables. The results indicate that reducing the cantilever length or decreasing the suspended mass effectively reduces system vibration.

Support matrix machine is an advanced matrix learning model that can fully utilize the intrinsic structural information in matrix data. However, it is susceptible to noise and outliers, and lacks generalization ability in imbalanced data. To this end, a robust cost-sensitive support matrix machine (RCSSMM) model is proposed and applied to intelligent diagnosis of wind turbine gearbox faults. RCSSMM improves the robustness to noise and outliers by evaluating the prior distribution of the matrix input with assembled matrix distance, and assigning different sample weights to different samples. Additionally, RCSSMM introduces the cost-sensitive loss function that assigns different penalty factors to different categories of matrix data. The optimal values of the penalty factors are adaptively determined with the Harris hawk optimization algorithm to focus on minority class samples and improve the diagnostic performance on imbalanced data. The proposed method is validated using simulated experimental data and real measured data of wind turbine gearboxes. The experimental results demonstrate that the RCSSMM model exhibits more outstanding fault diagnosis performance even under the presence of noise, outliers, and imbalanced data.

Real-time hybrid test has been applied to the performance test of high-speed train running on the bridge in recent year. In order to avoid the damage of specimens or loading systems caused by instability, it is necessary to study the stability of real-time hybrid test on traveling train-bridge system. The time-varying characteristic of the traveling train-bridge system poses challenges to the stability analysis of real-time hybrid test. Therefore, it is necessary to develop suitable stability prediction methods for the time-varying system. Firstly, the time-varying discrete state space equation of the real-time hybrid test on traveling vehicle-bridge system was established, which can accurately describe the changes of all state quantities of the test system over time. Then a stability criterion based on the spectral radius of the cumulative state transition matrix was proposed, and then by combining the stability criterion with the dichotomy method, a relative stability prediction method for the time-varying real-time hybrid test was developed. A serial of practical real-time hybrid tests on traveling vehicle-bridge system was conducted based on a shaking table. The results show that the critical stability obtained by the practical tests was in good agreement with the predicted results based on the developed stability prediction method. The developed method can accurately predict the stability of RTHT on vehicle-bridge coupled system.