In order to meet the requirements of high transmission efficiency and low noise in the planetary gear transmission system，the bending-torsion-shaft coupling power of helical planetary gear transmission system was established by employing the lumped parameter method，with considerations for eccentricity error and installation error. Using the fourth-order Runge-Kutta method to solve the dynamic equation，the dynamic characteristics of the planetary gear，such as the dynamic meshing force，dynamic transmission error，and dynamic load coefficient，were obtained. Based on this，the planetary gear modification research is carried out，and the tooth profile modification is established. Upon establishing the tooth surface equation and the dynamic equation that takes tooth surface modification into account，an analysis was conducted on the dynamic characteristics corresponding to varying degrees of modification. The research results show that with the increase of the modification amount，the dynamic meshing force，dynamic transmission error and dynamic load coefficient of the planetary gear all decrease to varying degrees，and then increase after reaching the lowest value. Performance testing of the entire machine revealed a reduction in vibration and noise of the planetary reducer，as well as an improvement in transmission performance providing theoretical support for the design of vibration reduction，noise reduction and transmission efficiency improvement of the planetary gear transmission system.

This paper introduces a method of structural modal parameter identification based on visual vibrometry. For continuous and long time sampling video，this method ensures the accuracy and resolution of measurement results by setting local “virtual” measurement points and enlarging video slices，and significantly improves the data processing efficiency. It includes several steps： recording a video of the test structure under external excitations； Setting a series of “virtual measurement points” at the edge of the structure by using edge detection algorithm； Extracting apparent motions of “virtual measuring points” using optical flow methods，and then identifying natural frequencies and modal damping ratios using the stochastic subspace method； Estimating the full-field operational mode shapes of the structure by applying motion magnification to cropped videos. Two real-life tests are conducted to validate the procedure： firstly，vibration test of a model aircraft excited by a single sinusoidal input is used，where the response peak appears in the same frequency with the known-input. Secondly，operational modal analysis of a cantilevered beam is conducted using visual vibrometry，in which the first five modal parameters are estimated and compared to the measurement results using a Scanning Laser Doppler Vibrometer. It is shown that the maximum relative discrepancies of the natural frequencies and damping ratios are only 0.35% and 14.6%，respectively，and the modal shapes are also observed in excellent correlation.

A novel method for nonlinear force reconstruction has been developed to reproduce the stick-slip friction contact behaviors of joint interface. Nonlinear substructure modeling is employed to simplify the complex jointed structures into the linear substructures and nonlinear joints. An inversion technique has been developed to eliminate the singularity of transfer matrix，extracting only the transfer relationship between the degree-of-freedoms of nonlinear joints and measuring locations. The harmonic balance method is used to directly apply the measured nonlinear dynamic responses of the linear substructures to reconstruct local hysteresis nonlinear contact forces of the bolted joint interface. Numerical simulations and experimental investigations of a lap-type bolted joint beam system have been performed to verify the nonlinear force reconstruction process，and to investigate the effects of stick-slip friction contact at the bolted joint interface. The good agreement between the comparison results validates the proposed nonlinear force reconstruction method，and the reconstructed nonlinear virtual excitation can be further used to detect the loss of bolt preload effectively.

Directed at the proposed earthquake reduction system，named the tuned tandem mass dampers （TTMD），the optimized analysis of the multi-degree-of-freedom （MDOF） structure-TTMD system has been investigated in frequency domain by the particle swarm optimization. The seismic simulation of the MDOF structure-TTMD system has been established under earthquakes. Considering different types of seismic records，the control efficiency of TTMD for the structural seismic responses was analyzed in the time domain and compared to that of the tuned mass damper （TMD） with the equal total mass ratio. Further taking into account the structural stiffness of the -10% and -30% degradations，the earthquake reduction behaviors of TTMD were scrutinized for the seismic responses of the structure with the stiffness degradation. It is found in terms of numerical results that the TTMD outperforms the TMD in seismic performance and robustness. Likewise，the TTMD has a drastically reduced damping demand，thus being an enhanced earthquake reduction system.

It focused on the test and simulation study on the longitudinal load transfer law under the coupling shock condition of a roadrailer. The bogie of this type of the vehicle contains the towing plate and the yaw damper device，which are oriented in the longitudinal direction. Therefore the load transmission path and its value need to be investigated for further strength evaluation of the structural component. In the test，force sensors were installed on the key components. In the simulation，a comprehensive whole vehicle dynamic model，which contains 3 carbodies and 4 bogies，was established based on the theory and method of the rail vehicle and multibody dynamics. Meanwhile the collider is simplified to a mass considering its mass and speed to simulate the locomotive. Besides，it gave the modeling details of the yaw damper device and the towing plate. By the SIMPACK solver，the results demonstrate that the forces on the hook and the yaw damper device both increase with the impact speed increasing. Furthermore，the simulation results were slightly smaller than the test results，but the law is nearly the same. Under these conditions，the yaw damper had no effect. Therefore，the transmission path is only through the towing plate，which is useful for further strength evaluation.

Complex multi-mode signals can be decomposed into single mode components using time-frequency decomposition technology. This allows for the use of a simple and reliable single mode identification method to identify the complex modal signals of mechanical structure. Empirical wavelet transform (EWT) method can effectively decompose the modes, and some revised methods even can overcome the strong noise. However, when reconstructing the modes, the reconstructed mode could be distorted due to overlapping filters and closely spaced components. Focusing on the problem of mode decomposition and reconstruction, this paper analyzes the problem of distorted reconstructed mode of EWT method, proposes a revised method based on the Iterative Truncated Singular Value Decomposition (ITSVD) method, and applies this new method to both the synthesis signal and the experimental signal from the vibration response of a mechanical structure model with a joint surface. The results suggest that the proposed ITSVD-EWT method is more effective in mode decompose and reconstruction.

Reaction wheels are not only important attitude control actuators for satellites，but also the most prominent onboard micro-vibration source. Considering the varying rotating speed of reaction wheels，this paper proposes a new vibration isolation method using a six-strut isolator combined with the electromagnetic shunt damping （EMSD） technique. A dynamic model of the coupled system consists of a reaction wheel and the isolator is derived including the gyroscopic effect produced by the rotating wheel. The results obtained through analytical analysis and simulations show that gyroscopic effects have a great effect on the natural modes，frequencies，and isolation performance. And then，the influences of key parameters on the isolation performance are analyzed and optimized. Finally，an isolation strut based on the EMSD technique is manufactured and tested. The experiment results verified the influences of the stiffness and EMSD on the transmissibility of the strut.

To enrich the measured database of the modal parameters of the long-span cable-stayed bridge，based on the data collected by the structural health monitoring system of the Sutong Bridge，the modal parameters of the bridge during 2010 are obtained using the established automated modal identification and tracking method. On that basis，the variability of the modal parameters of the bridge with the changing temperature and wind speed is analyzed. Results show that the frequency of the bridge is controlled by both temperature and wind speed. The frequency decreases with the increased temperature and increases with the increased wind speed. The variability of the damping ratio of the main girder of the bridge is significantly greater than that of the frequency. The damping ratio of the first-order lateral bending modes of the main girder fluctuates between 0.5% and 15% at low wind speed interval. It gradually decreases and stabilizes at about 2% when the wind speed is greater than 9 m/s. The damping ratio of the first four vertical bending modes of the bridge is mainly affected by the aerodynamic damping. It increases slightly with the increase of wind speed at the low wind speed intervals. The obtained results can provide a reference for assessing the in-service performance and issuing operational management of the bridge.

In order to solve the problem of complex nonlinear vibration response in the traveling vehicle system，a nonlinear dynamical model for a coupled human-vehicle-road system with three-degree-of-freedom is established. The coupled vibration equations of human-vehicle-road with three-degree-of-freedom are derived by the Lagrange equation，and the sine and cosine functions of this system arise from the geometric nonlinearity of torsional deformation. The nonlinear restoring force surfaces，potential energy surfaces and analytical expressions of natural frequency are obtained for the free vibration of the human-vehicle-road system. For the forced vibration，the influence of vehicle system parameters of vehicle mass，moment of inertia，passenger mass，seat stiffness，suspension stiffness，damping，centroid position，road wavelength and wave amplitude on the response curves of amplitude velocity is analyzed by using the numerical simulation method. The experimental platform of the coupled human-vehicle-road vibration system is built and the reliability of theoretical analysis and numerical results is verified by the experiments. The results show that this nonlinear dynamical coupled system with three degree-of-freedom can accurately describe the human-vehicle-road response characteristics，and reasonable selection of the system parameters can effectively reduce the vibration response amplitude and improve the human riding comfort.

With the advent of the era of big data，the mechanical equipment fault diagnosis method based on deep learning has attracted more attention. However，the traditional deep network model seriously limits its application in practical engineering due to the excessive amount of parameters and calculations. Based on this，a GhostConv lightweight network model is proposed and used for fault diagnosis. GhostConv generates a small part of the feature maps through conventional convolution，and performs multiple feature extraction on the generated feature maps to generate the remaining feature maps. Contact the feature maps of the two parts to obtain a complete feature map. GhostConv structure saves the cost of generating redundant feature maps in conventional convolution to the maximum extent，and reduces the model parameters to ensure the performance of the model. In the experiment，the continuous wavelet transform is used to transform the vibration signal to generate a two-dimensional time-frequency diagram，and then the designed GhostConv is used to establish a lightweight fault diagnosis network model. The original dataset and noisy dataset of Case Western Reserve University are used for experimental verification，and compared with the conventional convolution structure network model and depth separable convolution structure model in terms of parameters，calculation and recognition rate. The experimental results show that the GhostConv lightweight network model still has high recognition accuracy and strong anti-noise ability under the condition of fewer parameters and calculations with good robustness and generalization ability. The parameters of the model are only 6% of the conventional convolution model and 56% of the deep separable convolution model. Under the condition of strong noise interference，the fault diagnosis and recognition rate is still higher than that of the conventional convolution model，which confirms its engineering application value.