A magnetorheological elastomer （MRE） vibration absorber is designed to suppress the vibration of industrial robotic milling in order to solve the low frequency chatter problem. The magnetorheological effect of MRE with different mass ratio is studied by using the unique rheological characteristics of MRE. The number of turns of coil and the current in the absorber are determined by theoretical calculation and numerical simulation. It is found that the designed MRE absorber has frequency shift characteristics in the range of 17.35~45.21 Hz through modal simulation and shaking table sweeping excitation experiment. The mapping relationship between natural frequency of absorber and current is established，which is verified by experiments in the milling process of KUKA KR500 robot. The results show that the robot is prone to chatter at its low order natural frequency under low rotational speed machining conditions，and the chatter suppression of the robot is realized by MRE absorber. Compared with the condition without vibration absorber，the peak-to-peak value of the vibration acceleration in the X direction of the robot spindle is reduced by 70.7%，and the root-mean-square value is reduced by 64.7% after being electrified. The peak-to-peak value in the Y direction is decreased by 54.7%，and the root-mean-square value is decreased by 49.9%. In addition，the machining surface quality of workpieces after milling has also been significantly improved.

Existing S-transform-based load spectrum editing methods for automotive components suffer from the problem of lack of adaptivity in time-frequency resolution，which affects the time-frequency aggregation of load spectrum energy and leads to poor editing results. To solve this problem，based on the theory of generalised S-transform （GST），the application of GST method in the field of automobile components load spectrum editing is explored. The GST method is used to perform time-frequency analysis of the mount load spectrum to obtain the distribution information of the load energy on the time and frequency axes. The accumulative power spectral density （APSD） of the load spectrum is calculated，and a genetic algorithm is used to determine the threshold value of the APSD in order to identify the time segments of the load spectrum with smaller damage contributions. The time segments of the load spectrum with small damage contributions are identified and removed，and the remaining load time segments are spliced to obtain a compressed load spectrum. Comparing with the load spectrum editing method based on S-transform，it is found that the time compression of the compressed load spectrum obtained based on the GST method is larger，and the compressed load spectrum basically matches with the original load spectrum in terms of statistical parameters，power spectral density，rainflow counts，fatigue life and damage distribution. The results show that the GST method is suitable for editing the load spectrum of automotive components. It can provide an effective means to improve the efficiency of durability bench tests of automotive components.

The tire deformation traveling wave characteristics vary at different vibration frequencies and speeds，and are influenced by the coupling of landing gear structural vibration，resulting in continuous changes in tire lateral deformation modes. The tire models for previous traditional landing gear shimmy analysis are quasi-static restoring force model，which assumes that the functional relationship between tire lateral force，self-aligning moment and lateral deformation is fixed. Based on the tire stretched string theory，a time delay tire model coupled with landing gear shimmy is established to analyze the dynamic changes in tire lateral deformation modes，and the real-time lateral deformation distribution of the tire and the nonlinear dynamic behavior of the landing gear during shimmy are obtained. The time delay is introduced to calculate the tire deformation traveling wave，and the stability of the landing gear tire coupled shimmy model is studied by the bisection method. The testing methods for the parameters of time delay tire shimmy model is provided. Using the methods presented in this paper，the landing gear shimmy analysis and experimental test of a certain aircraft are conducted. The calculated vibration frequency and shimmy stability region are consistent with the analysis results of traditional tire models and test results.

In order to consider the effect of liquid sloshing in an annular water tank on mechanical performance of a two-stage variable damping TMD，taking an actual high-rise structure as an example，a global model considering the water tank as a particle and the liquid-solid coupling model of the water tank under the full water state and the non-full water state are established by ABAQUS software. The seismic responses of the two-stage variable damping TMD under different liquid-solid coupling states are compared and analyzed. The results show that the amplitude and maximum damping force of the two-stage variable damping TMD considering liquid sloshing are larger under larger seismic excitation，and the sloshing effect of liquid inhibits the full development of the second-stage damping energy consumption of the two-stage variable damping TMD. With the increase of seismic excitation，the maximum base shear force of the liquid-solid coupling model is larger than that of the particle model，and the relative increase amplitude increases accordingly.

In order to improve the energy dissipation capacity of the irregular steel joints of pseudo-classic architecture，the replaceable viscous damping device was set up at the location of decorated bracket to dissipate seismic energy. Six specimens of pseudo-classic architecture joints were designed and manufactured，including the single beam-column joint （SBJ） series and double beam-column joint （DBJ） series. The hysteretic curves and skeleton curves of the specimen and the viscous damper were obtained by the sine wave dynamic loading with displacement and frequency control，and the deformation and energy dissipation capacity of the specimen and the viscous damper were analyzed，respectively. The results indicate that the improved dynamic loading system has achieved good test results，and the failure mode of the irregular steel joint of pseudo-classic architecture is improved by installing a viscous damper at the decorated bracket position. The viscous damper has good working state after buckling in the plastic hinge area of the beam end of the specimen，and the hysteresis ring of the specimen becomes full gradually. The larger the damping coefficient of the damper，the fuller the hysteresis rings of the node and the stronger the energy dissipation capacity. With the increase of damping coefficient，the bearing capacity of specimens with controlled joints is increased by 18%~46% compared with that of without controlled，and the viscous damper increases the bearing capacity of specimens with double beam-column joints more significantly. The displacement ductility coefficient of the specimen is between 1.77 and 2.05，and the ductility of the specimen is slightly improved after the viscous damper is installed. The strength degradation coefficients are all about 1.0.

The harmonic vibration produced by the gear meshing in the helicopter’s main reducer is one of the main sources of noise in the helicopter cabin. Designing vibration-isolating gearbox struts to suppress vibration transmission to the airframe can effectively reduce cabin noise. The piezoelectric stack actuators periodic strut （PSAPS），composed of periodically arranged piezoelectric stacks and metallic materials，demonstrates ‘mechanical filtering’ characteristics within specific frequency bands，serving as a passive vibration control method. By adjusting the driving voltage of piezoelectric stacks in PSAPS to achieve variable stiffness characteristics，active vibration control is enabled. In order to study the electromechanical coupling relationship between active vibration control and passive vibration control of PSAPSs，a specialized PSAPS configuration is developed to address helicopter gear meshing noise suppression，and the electromechanical coupling dynamic model of PSAPSs with the form of transfer matrix is established for the mechanical filtering characteristics of periodic structure and elastic wave propagation in piezoelectric stack. In frequency domain，the force and velocity at both ends of the PSAPSs，the driving voltage and current，the geometrical parameters of the strut and the material parameters are coupled in this model. In this paper，the maximum attenuation rate of the PSAPS can be obtained under the limitation of the maximum driving voltage and current of the piezoelectric stack by using this model. The influence of rubber damping loss factor，excitation force，and cell number in PSAPS on the required driving voltage and current for active control is analyzed in this article.

Based on the problems of poor interpretability，as well as parameter increase and memory consumption caused by blind stacking layers in traditional fault diagnosis method based on deep learning，Neural ordinary differential equation （NODE） is introduced into mechanical fault diagnosis，the network structure of NODE for machinery fault diagnosis is constructed. In the constructed structure，the derivatives of the parameterized hidden states of the neural network are used to replace the discrete sequences of the specified hidden layers. By constructing a nonlinear relationship between fault data and fault types，an ordinary differential equation solver （ODE solver） is used to complete the classification of different fault types，and an end-to-end fault diagnosis model is formed. The proposed method is applied to mechanical fault diagnosis to build a specific NODE network model，and the classification task of different fault categories is accomplished through the input of fault data. The constructed model is applied to the fault diagnosis of spindle bearing in the aircraft engine，and compared with the fault diagnosis method based on residual network model. The experimental results show that the constructed model and residual network model have satisfactory accuracy. However，the constructed model not only reduces the memory consumption，but also reduces the number of model parameters by almost five times.

To accurately extract fault feature information under strong background noise，a multi-scale improved differential filter （MIDIF） is proposed for rotating machinery fault diagnosis. The rotating machinery vibration signal is decomposed into a series of multi-scale improved differential filter signals using MIDIF. In view of that the MIDIF filtered signals exhibit varying extents of validity in revealing fault features，a weighted reconstruction method using correlation analysis is proposed in which the weighted coefficients are counted and distributed to the corresponding MIDIF filtered signals to highlight the effective MIDIF filtered signals and weaken the invalid ones. The weighted coefficients are multiplied with the MIDIF filtered signals under different scales to produce transient impulse components. The fault types of rotating machines are inferred from the fault defect frequencies in the envelope spectrum of the transient impulses. The results show that MIDIF is more accurate in extracting fault features than multi-scale average combination different morphological filter （ACDIF） and multi-scale morphology gradient product operation （MGPO），and that it provides an effective method for rotating machinery fault diagnosis.

In order to improve the intelligence of fastener disease diagnosis，a fastener condition diagnosis method is proposed based on vehicle dynamic response data and generalized demodulation time-frequency analysis combined with sparrow search algorithm-support vector machine （SSA-SVM） model. The acceleration signals of the normal and abnormal sections of the fastener are collected，and the short-time Fourier transform and the maximum overlapping discrete wavelet packet transform are used to preprocess the signal data. The generalized demodulation time-frequency analysis method is used to decompose the signal，and the effective value，energy contribution rate and wavelength of the main information components are calculated as the characteristic index. The characteristic index is trained by the joint SSA-SVM model to construct the classification model. The results show that the accuracy of the method is 97.50%，and several evaluation indicators are used to verify that its effectiveness and accuracy can meet the actual needs.

Combined with the long-term observation data of three-dimensional ultrasonic anemometer at the deck of a long-span suspension bridge in the coastal area of Guangdong Province，the average wind characteristics of the wind field at the bridge site are statistically analyzed. Taking the wind speed exceeding 8 m/s as the standard of strong wind，the fluctuating wind characteristics of the bridge site are analyzed based on strong wind samples. The results show that the coastal areas of Guangdong are mainly affected by the southeast monsoon in spring and summer and the northwest strong wind in autumn and winter. The downwind turbulence intensity is obviously greater than the transverse wind and vertical turbulence intensity，and the ratio of each component is roughly I_u∶ I_v∶I_w=1∶0.86∶0.60. There is a significant positive correlation between gust factor and turbulence intensity，and the empirical formula recommended by Cao and Choi can better reflect the relationship between the two，and the empirical formula recommended by Cao is more suitable for coastal areas. Turbulence integral scale has a negative correlation with turbulence intensity. With the increase of turbulence intensity，turbulence integral scale first decreases rapidly and then tends to be stable. Based on the measured data，the empirical formula of turbulence integral scale and turbulence intensity is given，and the correlation between the two is significant. In the measured data，the downwind power spectral density is in good agreement with Kaimal spectrum，the transverse wind power spectral density is in good agreement with Von Karman spectrum，and the vertical power spectral density is in good agreement with Panofsky spectrum at high frequency band.