The full-field vibration displacement acquired via digital image correlation method is widely applied in aerospace structural testing and monitoring because of its advantages of high environmental adaptability and non-contact full-field. However，structural damage identification based on full-field vibration displacements faces two critical problems： Current modal analysis methods possess low computational efficiency when dealing with high spatial resolution displacement fields； The baseline-free damage identification method based on modal shape is difficult to extract damage features and has poor anti-noise performance. In order to solve those problems，a frequency domain modal analysis method based on kernel decomposition and joint principal component analysis，and a damage localization method based on pseudo-excitation are proposed. Singular value decomposition is employed to process the full-field displacement fields for obtaining the kernel functions and their coefficients，which contain the local damage characteristics. On this basis，a frequency domain modal analysis enhanced by joint principal component analysis is adopted to evaluate the noise-robust and high spatial resolution modal shapes. The disturbance of local dynamic equilibrium equation caused by structural damage is equivalent to a pseudo excitation force for damage detection. In addition，the local proximity of damage features and sparse spatial distribution of measurement noise are harnessed to optimize the damage localization accuracy via a hierarchical clustering method. Multi-modal information fusion damage index is proposed to improve the accuracy of damage localization. Numerical and experimental results demonstrate the effectiveness of the proposed method.

In order to apply active dry friction dampers （DFD） to the vibration control of rotor system，a model free adaptive force control scheme is proposed，where virtual feedback tuning method is exploited to tune the initial parameters. Vibration characteristics of the active DFD-rotor system are analyzed based on a two-dimensional dry friction dynamic model. And vibration control strategies are proposed to match the response characteristics of rotors. Then，a compact-form dynamic linearization model is applied to design model free adaptive control algorithm. Meanwhile，considering the cumbersome work of initial parameter tuning，a virtual reference feedback tuning procedure is used to initialize parameters for the controller and the rules to choose parameters used for off-line data generation is also discussed herein. In order to verify the efficacy of the proposed algorithm，a rotor system containing two discs is taken as the numerical example. Results reveal that，based on one single off-line parameter tuning procedure，the rotor vibration when critical speed is traversed can be efficiently controlled by the proposed control strategy. Meanwhile，for steady vibration control，the proposed strategy is able to adaptively apply controllable forces only if the vibration level is too large，in which case the unbalanced responses of rotors can be sustained within allowable range.

A double Gamma distribution model to determine the probability density function （PDF） of the time domain rainflow-range corresponding to the broadband random stress power spectral density （PSD） is proposed，and a neural network method is used to implement the parameter prediction of the model. A series of stress PSDs are given，and the corresponding stress time histories are generated using the time-domain randomization method. The number of rainflow-range is counted for the stress time histories using the rainflow counting method，and the stress rainflow-range probability density values are calculated. Based on the calculation results of each stress PSD mentioned above，the proposed stress rainflow-range probability density double Gamma distribution model is parametrically fitted to obtain a set of corresponding model parameters. The results of the double Gamma distribution model are compared with the Dirlik method and fatigue life prediction is carried out，and the results show that the proposed double Gamma distribution model is more accurate for determining the broadband random stress rainflow-range PDF.

In order to improve the energy absorption and safety of the energy absorption hydraulic support，a multi-layer lattice energy absorption device is designed. The basic structure of pyramid lattice energy absorption device is designed according to the structure and energy absorption space of energy absorption support column. The maximum energy absorption of the energy absorption device，the maximum mean of the support force within the allowable range，and the minimum fluctuation coefficient of the support force are taken as the optimization objective function，the base diameter and span of the pyramid cell are taken as the optimization design variables，and the constraint conditions are taken as the peak and mean of the support force of the energy absorption device within the allowable range. The Workbench software is used to optimize the structural parameters of the energy absorption device with the pyramid height of 30 mm，40 mm and 50 mm respectively. Three groups of optimization solutions are obtained and the optimal structural parameters are determined by comparative analysis. The single-layer energy absorption device with the optimal parameters reduced in the compression experiment was used for experimental analysis，and the results show that the absorption energy is 4.18716 kJ. The calculated energy absorption energy of the original single-layer energy absorption device is 113.05332 kJ，and the energy absorption energy of the whole energy absorption device is 565.2666 kJ. The relative error between the experimental results and the simulation results is only -9.92%. The energy absorption capacity of the new energy absorption device is at least 50% higher than that of the traditional thin-wall structure energy absorption device，which proves the effectiveness of the optimized design and the high energy absorption capacity of the energy absorption device.

To address the issue of carrying rolling element bearing （REB） fault diagnosis where the conventional vibration sensor is difficult to install，an instantaneous angular speed （IAS） signal based REB fault diagnosis method by optimized AR model is proposed. The forward differential method is used to calculate and estimate the instantaneous angular speed signal. Then，the biased estimation autocorrelation analysis is used to determine the optimal order p by the maximum autocorrelation kurtosis. Periodic components in the IAS signal are removed by AR prediction，and the residual components containing rich bearing fault information are remained. The residual components are pre-whitened to equalize the importance of each band and to extract fault characteristics from the envelope. Simulation signal and outer ring data from a test rig validate the effectiveness of the proposed method. The experimental comparative analysis results show that the calculation efficiency is improved significantly when compared to the existing method of fast spectral steepness combined with order analysis based on vibration signal.

The graph neural network models have been widely used in the field of fault diagnosis due to the advantage of abundant fault characterization capabilities. However，the existing models only utilize the local information among neighboring nodes when dealing with fault data，and fail to fully extract the global feature information. Meanwhile，in order to overcome the problems of low accuracy and insufficient generalization ability of single model. This paper proposes an ensemble method with multi-scale graph pooling feature fusion and graph convolutional network （MSGP-GCN）. The graph model is constructed from the original signal，and global information is obtained using graph pooling coarsening. Then weights are assigned at different scales based on the degree of the nodes，and the global information is used to update the node features in combination with the weights. The updated node features are input into different classifiers respectively，and the intelligent fault diagnosis result is obtained by majority voting strategy among these classification results. The proposed approach is fully verified by two fault datasets，the SEU simulation dataset and the real coal mill dataset. The experimental results show that the proposed model can effectively improve fault diagnostic accuracy and generalization ability in aforesaid two real datasets，and the average diagnostic accuracy reaches 98.31% and 97.21%，respectively.

Aiming at the problem that the recognition accuracy of the model is not high due to the complex and variable engineering environment，a rolling bearing fault diagnosis model integrating Markov transition field and graph attention networks （MTF-GAT） is proposed in this paper. Using the advantage of MTF to retain the time correlation of the signal is applied to transform one-dimensional signals into two-dimensional feature maps，and the nodes and edges of the graph are defined. The graph attention layer can adaptively assign different weights to adjacent nodes to improve the ability of the model to capture useful fault features，and the abstract information of the graph is further extracted through the deep convolution module. By simulating the actual engineering environment，the various fault signals are input into the trained MTF-GAT model for fault diagnosis，and the model is verified by experiments on two data sets. The results show that the proposed model in this paper can accurately complete the task of fault classification in a variety of environments. Compared with other deep learning models，the MTF-GAT model has better recognition accuracy and generalization performance.

Milling vibration problems can increase tool wear and reduce part machining accuracy，the suppression of which is a hot research topic in the field of milling. In order to suppress forced vibration in milling and enhance the stability of the machining system，a spindle-tool system is proposed based on electromagnetic actuators technology. The electromagnetic actuators are mounted in the spindle-tool system and acts on the toolholder position，using its controlled electromagnetic force for vibration suppression. Firstly，the structure and working principle of the system is described and the milling dynamics of the system is modelled. Secondly，based on the working principle of electromagnetic actuators，a PD controller is designed and the dynamic model and controller are simulated and verified. Finally，machine vibration signals are collected and external excitation experiments are carried out on a rotor test bench simulating tool process. Simulation and experimental results show that the spindle-tool system based on electromagnetic actuators under PD control law can effectively suppress the forced vibrations during the milling process.

Aiming at the problem of the multi-order modal vibration of flexible wind turbine tower，a self anchored damping cable is designed in this paper，which converts the angular displacement of tower bending vibration into linear displacement，and drives the damper to dissipate energy and reduce vibration. Firstly，the tower-damper-cable vibration equation is established，and the analytical solution of the additional damping ratio provided by the damper cable for the first two-order bending vibration of the wind turbine tower is obtained. Then，the relationship between the damper viscosity coefficient and the additional damping ratio provided by the damper cable for the first two-order modal vibration of the wind turbine tower is analyzed through model experiment. The results show that the damping cable can provide a large additional damping ratio for the first two-order bending vibration of the tower，and the analytical solution of the additional damping ratio is in good agreement with the experimental results. Finally，based on the theoretical calculation formula of additional damping ratio，the influence of parameters on the damping performance of damping cable is analyzed.

In order to solve the problem of seismic design of continuous beam bridge in which the longitudinal seismic inertia force is only carried by the fixed pier，the seismic potential of the movable pier is fully exerted with the same section as the fixed pier. Based on the principle of wrap rope，the mass rotation wrap rope device excited by additional mass inertia force is developed to realize the cooperative force of fixed pier and movable pier and limit the relative displacement of beam end. Based on the working principle and structural characteristics of the device，the restoring force model of the device is proposed，and through a 3-span regular continuous beam bridge，the finite element model of the whole bridge is established. The effects of additional mass，friction coefficient and initial relaxation coefficient on the vibration reduction performance of continuous beam bridge are systematically analyzed. The results show that the effect of mass rotation wrap rope device on reducing the seismic response of fixed pier and lifting the movable pier to participate in the longitudinal whole cooperative force of continuous beam bridge is obvious. The influence of parameters of different seismic wave input characteristics is slightly different，but reasonable design parameters of the device will produce a more obvious effect of shock absorption.