A polynomial dimensional decomposition pseudo-excitation method (PDD-PEM) was established in the frequency domain to quantify the uncertainty of random vibration power spectrum density for vehicles with uncertain parameters under random road excitation. Transforming stationary random vibration analysis into harmonic load analysis through pseudo-excitation method, and transforming double random problems into single random problems; At the same time, the polynomial dimensional decomposition method is used to construct a random Surrogate model, and the explicit function of the power spectrum density response expressed by the polynomial basis is given, which effectively realizes the probabilistic evaluation of the structural response in the uncertain parameter space. In numerical examples, the method established in this paper was used to analyze the random vibration of vehicle systems with uncertain parameters under road roughness. Compared with the Monte Carlo method, the correctness and effectiveness of the established method were verified, and the influence of uncertain parameters on the structural response statistical characteristics was further discussed. These works laid a certain foundation for considering the optimization and control problems of vehicle system parameters with uncertainty.

The fractional nonlinear Zener model is used to describe the nonlinear and viscoelastic constitutive relation of the vibration isolation system. The variation law of system amplitude-frequency response and backbone under the combined action of constant excitation and harmonic excitation is discussed, and the influence of constant excitation on the dynamic behavior of vibration isolation system is discussed significantly. The fractional-order derivative term is made equivalent to a term in the form of trigonometric function, the steady-state response of the system is solved by harmonic balance method, and the results are compared with a variety of other methods. The influences of different parameters on the coexistence frequency band range of the amplitude-frequency response multi-state solution are summarized, and the dynamic behaviors of the system under the combined excitation are obtained by using numerically simulation. The results show that there are five solutions co-existence region in the amplitude-frequency response solution under the combined effect of constant excitation and harmonic excitation, and the system shows a phenomenon of coexistence of softening characteristic and hardening characteristic, and the backbone of the amplitude-frequency curve is tilted firstly to the left and then to the right. Additionally, it is found that the periodic motion and chaos coexist in the system under the combined excitation, and the transition laws of the polymorphic coexistence region and its adjacent regions are summarized explicitly. Affected by constant excitation, the diversity of periodic motion of the system under the combined excitation is significantly different from the dynamic behavior under the action of simple harmonic excitation alone, and the transition rules of periodic motion of the system under the action of combined excitation are summarized based on the Lyapunov exponent.

Environmental microvibration affects the accuracy of precision instruments, making microvibration measurement and assessment crucial. Microvibration level measurement is based on the octave spectrum of the velocity signal. However, the frequency-domain FFT method used in traditional octave analysis suffers from shortcomings such as fixed resolution and low-frequency spectrum leakage. Therefore, a complex-analysis ZFFT correction algorithm based on ratio correction was proposed. Simulations show that this algorithm improves spectral resolution while maintaining the same number of FFT analysis points. While maintaining the same number of sampling points, the computational effort is significantly reduced, and the spectrum amplitude error is as low as one thousandth. Frequency-band octave analysis is employed to suppress low-frequency spectrum leakage and increase the number of spectral lines. A microvibration monitoring and analysis system was developed, comprising a low-frequency microvibration sensor, the MI-7208 intelligent measurement device, and microvibration level measurement and assessment software. Field measurements verified the system's ability to detect VC-F-level microvibration signals and its long-term measurement stability.

Traditional computer vision methods usually focus on the in-plane dynamic response of structures. Therefore, this paper proposes an image phase-based stereo matching temporal analysis method to achieve targetless robust monitoring of three-dimensional structural deformation. This method uses 2D-Gabor filters and Gaussian pyramid gradient algorithms for image preprocessing, applies a phase-based dense optical flow tracking algorithm and an improved semi-global block matching (SGBM) algorithm to realize full-field measurement of structural displacement in the region of interest, and further proposes an intuitive displacement-strain conversion method to measure three-dimensional strain of structures. Through virtual reality experiments based on physics-based graphics models (PBGM), it is verified that the error of this method compared with 3D-DIC and finite element analysis deformation is less than 2%; in vibration tests of outdoor bridge structures in the laboratory, the deformation error compared with traditional testing methods can be controlled within 8%, meeting engineering application accuracy. Without compromising accuracy, this method achieves targetless robust monitoring of three-dimensional structural deformation, and better solves the problems of large environmental impact and high cost in traditional structural deformation monitoring.

Quasi-zero-stiffness (QZS) isolators have excellent vibration isolation performance in the low-frequency range. However, in complex excitation environments, such as load mismatch condition, vibration isolation performance and corresponding stability deteriorate. To improve the vibration isolation performance of electromagnetic zero-stiffness isolators (E-QZS) and reduce the sensitivity to load, a load adaptive sliding mode control method of E-QZS is proposed. The theoretical model of an electromagnetic zero-stiffness isolator is established and a sliding mode control is designed. The range of gain coefficients for stable operation is determined using Lyapunov’s theorem. Additionally, we have devised a load-adaptive control law and conducted a corresponding stability analysis. Through simulation and experimental research, the results demonstrate that setting appropriate gains can enhance vibration isolation performance by 90%. Furthermore, the introduction of a load-adaptive sliding mode controller effectively reduces the impact of sudden load changes on isolation performance, thereby improving the robustness of the isolation system.

There are a large number of ultra-large slope bridges in the rack railway line，and the settlement of bridge piers is difficult to avoid. It leads to the decrease of the smoothness of the railway line and threaten the safety and smoothness of the train. To solve this problem，based on the theory of vehicle-rack（track）-bridge dynamic interaction and gear dynamics，a coupled dynamic model of mountain vehicle-rack（track） -bridge system is established. The dynamic model considers the nonlinear meshing behavior of gear-rack and nonlinear contact behavior of wheel-rail in detail. The meshing behavior of gear-rack and the dynamic characteristics of vehicles under three different pier settlement modes （single pier settlement，continuous pier settlement and spaced pier settlement） are investigated，and the influence of different pier settlement modes on the vibration of vehicles is compared. The results show that the influence of pier settlement on the rack railway system is mainly reflected in the vertical and longitudinal acceleration of the vehicle，and the main frequency of vibration is 1~2 Hz and 8~9 Hz respectively. The effects of single pier settlement on the basic vibration characteristics of the rack-bridge system are similar to those of double pier settlement. But compared with double pier settlement，the effects of single pier settlement on the longitudinal acceleration of the vehicle are more significant，and the fluctuation of the meshing frequency is also significantly increased. Pier settlement will cause the increase of gear offset，and then lead to the instability of gear-rack meshing. When pier settlement is 6 mm，the problem of meshing apart begins to appear，which seriously threatens the operation safety of vehicles.

Since current loudness models are unable to predict loudness under round window stimulation，a loudness model for round window stimulation is proposed in this paper. The loudness model consists of a peripheral auditory model and a data processing back-end. The peripheral auditory model that is able to calculate basilar membrane velocities under free-field acoustic stimulation and round window stimulation and the back-end that transforms basilar membrane velocities into loudness are constructed. The reliability of the peripheral auditory model is verified by comparing the model-predicted results with the experimental data on the outer ear transfer function，middle ear transfer function and stapes velocities under acoustic stimulation，round window stimulation transfer function，frequency selectivity and frequency response of the basilar membrane，and basilar membrane displacement. The reliability of the loudness model is verified by comparing the model-predicted results with the experimental data on equal-loudness contours，bandwidth noise loudness，loudness level of tone with frequency masking，and threshold for complex tones. The results indicate that the loudness model accurately calculates basilar membrane velocities under acoustic stimulation and round window stimulation，and is able to predict the loudness of pure tone，complex tones，and bandwidth noise under acoustic stimulation and round window stimulation.

Recent earthquake damage investigations found that a large number of reinforced concrete frame buildings were heavily destroyed at beam-column joints and columns，without forming the beam-hinging mechanism expected in the design. Installing reinforced concrete wing walls beside the existing columns remains a fundamental and effective strengthening method，by improving seismic performance of both the columns and the joints，while promoting a beam-yielding mechanism. Two 1/2-scale frame specimens were manufactured，and one of them was strengthened by post-installation wing wall. By quasi-static tests，hysteretic behaviour，deformation capacity，energy dissipation power and failure mode of the two specimens were examined. The results show that the stiffness，bearing capacity and energy dissipation capacity of the strengthened frame were significantly improved. After strengthening，failure mode of the frame was changed from joints shear failure to expected beam-hinging. The efficiency and applicability of wing wall installation method were validated for strengthening existing frame structure buildings with seriously weak beam-column joints.

Helicopter cabin noise negatively impacts cabin environmental comfort and safety. In this paper，non-dominated sorting genetic algorithm Ⅱ is used to solve the electro-acoustic device placement problem of the active control system applied in the cabin. An appropriate spatial discretization of the sound field of the confined space is preformed，and then the electro-acoustic devices placement optimization problem，quantity optimization problem，and secondary source sound intensity optimization problem are further transformed into a combinatorial optimization problem. Taking the minimun value of the sum of the squares of the acoustic pressures at the measurement points as the control objective，the multi-objective optimization algorithm combined with the active control algorithm is adopted to solve the optimal placement of electroacoustic devices in the system. Considering the noise control system’s complexity and feasibility and limited space inside the cabin，the control system’s secondary sound sources and error sensors are selected as a 4-channel configuration. The optimization program is repeated several times independently，and the most frequently occurring positions of electroacoustic devices are counted，based on which computer simulation and experiment are conducted，and the results show that the optimization results can make the noise reduction at the height of the head of the cabin personnel in the sitting position reach up to 24.9 dB，and the global noise reduction reaches 19.4 dB.

Aiming at the problems of bearings working in complex environments，where fault data are difficult to obtain in large quantities and the serious imbalance between the ratio of normal data and fault data resulting in insufficient in-depth model training and low diagnostic accuracy，a bearing fault diagnosis method based on LSGAN-Swin Transformer is proposed. The least-squares generative adversarial network is utilized to expand the imbalanced or lack of bearing dataset，and the windowed self-attentive network is introduced for bearing fault state identification. The proposed method is validated by using two date sets，and compared with SGAN and WGAN respectively. It is demonstrated that LSGAN generates data training models with higher accuracy. The proposed Swin Transformer （Swin-T） model is compared with CNN，AlexNet and SqueezeNet under small sample conditions，and the accuracy is improved by 34.85%，13.45%，and 12.95%，respectively. The classification effect of the model is evaluated by t-SNE visualization，and the results show that the LSGAN-Swin-T model can still meet the requirements in fault diagnosis better when the number of training samples is small，which provides a new idea for the research of bearing fault diagnosis under unbalanced data.