Traditional algorithms are difficult to effectively separate and extract the composite fault features of bearings with overlapping resonance bands, an adaptive rolling bearing composite fault feature separation and extraction method combining adaptive variational mode extraction (AVME) and optimized multi-point optimal minimum entropy deconvolution adjusted (OMOMEDA) is proposed in this paper. The initial value of the center frequency of the VME parameter is determined by using the autocorrelation energy spectrum of S transform spectrum, and the desired modes related to the fault are extracted. Then the desired modes are linearly superimposed to reconstruct the original signal to realize the noise reduction of the signal. Extract periodic pulse signals from the reconstructed signal using OMOMEDA, and obtain fault characteristic frequencies by combining with envelope demodulation. The simulation and test signals verify that the method can effectively separate and extract the composite fault features of bearings with overlapping resonance bands. And compared with four other existing algorithms such as VMD-MCKD, the superiority of the proposed method is demonstrated.

When the finite element method is employed to calculate the mechanical behaviors of a corrugated sandwich panel structure, the numerical model occupies a large amount of computational resources, which usually causes the problem of long-time solution. In order to reduce the scale of the finite element model and to quickly perform the dynamic analysis of such type structures, in this paper the middle corrugated sandwich layer is simplified into a homogeneous orthotropic plate. Then, based on the third-order shear deformation theory, the equivalent stiffness matrix of the corresponding laminated plate element is formulated from adequate performance analyses of the corrugated sandwich plate. Afterwards, the natural frequencies of two corrugated sandwich plate structures in typical boundary status are obtained respectively through the test and numerical calculation. By comparing with the experimental results, the effectiveness of the equivalent finite element model is verified. It turns out that the obtained results are much better than those based on the first-order shear deformation model. Moreover, the method proposed in this work can be utilized efficiently for modal parameter computations of the corrugated sandwich plates with the high accuracy.

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.

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.

In this paper, a new concentrated mass-bent beam model of aircraft pylon is proposed, which is an effective mode reduction method for the analysis of vibration characteristics of continuous structures of pylon. Firstly, according to the periodic structure and the stress characteristics of pylon structure under actual working conditions, pylon structure is simplified into a concentrated mass-bent beam model which consists of 12 mass elements and 11 beam elements in series by using the concentrated mass method. The two simply supported boundary conditions reflect the true constraints of pylon-wing front and rear lifting points. The transfer equation and characteristic equation of the model are established based on the transfer matrix method. After using the parameter sensitivity method to correct and optimize the uncertain parameters of bending stiffness, the effectiveness of pylon concentrated mass-bent beam model is verified by comparing with the lower order natural frequencies of the finite element model. On this basis an engine is connected to the front and rear lifting points of pylon-engine through the installation section as the basic excitation, and engine-pylon concentrated mass-bent beam coupled model is established. Transfer matrix method is applied to study the natural frequency of the coupled model and the vibration response of pylon structure under the take-off, cruise and flight idle conditions of the engine. The vibration envelope lines of pylon structure mass elements under different conditions and different times and the vibration response of the representative mass element are obtained. In addition, the effectiveness of the new model is further verified by comparing with the finite element method. The research results provide theoretical support for the vibration reduction design of the pylon structure.

The vibration and radiation noise caused by the mechanical power equipment running on the ship have great harm, and seriously reduce the stealth performance and combat ability of the ship. The feedforward control algorithm which depends on the precise model will fail due to the adverse factors such as the long running of the power plant without stopping or the external impact. The traditional method of on-line system identification using auxiliary white noise not only reduces the control performance, but also increases the convergence time of the identification process. The method proposed in this paper uses the control signal to model the controlled system required by the FxLMS algorithm online in the noise frequency band, with faster convergence speed and identification accuracy. When the controlled system changes abruptly, that is, when the phase frequency characteristics of the controlled system change beyond ±90°, the algorithm can also track the changes of the system in real time and maintain the stability of the control. The active vibration control of the single-layer power unit vibration isolation platform was studied. The experimental results showed that the online identification of FxLMS control algorithm achieved 20.44 dB noise reduction at the motor operating frequency (50 Hz) when there was no secondary path model. The on-line identification algorithm can also maintain the control stability and quickly identify the changes in the phase frequency characteristics of the system after the mutation of secondary path.

The seismic performance tests of reinforced concrete (RC) shear walls and BFRP bars reinforced concrete (BFRP-RC) shear walls with different horizontal reinforcement ratios (0.25% and 0.50%) were carried out to explore the similarities and differences in seismic performance between RC and BFRP-RC shear walls. And the horizontal reinforcement ratio was expanded to 0% and 1.00% in meso-scale numerical simulation. The influence of reinforced materials type on the seismic performance of shear walls was discussed, and the shear capacity, deformation capacity, energy dissipation capacity, stiffness and recovery performance of RC and BFRP-RC shear walls were compared. The test results show that the shear failure and compressive shear failure occurred respectively in the shear walls with horizontal reinforcement ratios of 0%~0.25% and 0.50%~1.00% under horizontal cyclic load. The horizontal reinforcement ratio has the same effect on the failure mode, shear capacity, deformation capacity and energy dissipation capacity of RC shear wall and BFRP-RC shear wall; that is, increasing the horizontal reinforcement ratio can enhance the seismic performance of shear walls. However, the seismic performance of RC and BFRP-RC shear walls is different. Under the two horizontal reinforcement ratios, the shear capacity of the BFRP-RC shear wall is about 74%~78% of that of the RC shear wall, the deformation capacity is about 47%~84%, and the initial stiffness is about 77%~84%. Because the BFRP bar is always in the elastic deformation stage during loading, the recoverability of the BFRP-RC shear wall is significantly stronger than that of the RC shear wall. When the horizontal reinforcement ratio is 0.25% and 0.50%, the residual deformation of BFRP-RC shear walls is 62% and 13% of that of RC shear walls, respectively. The recoverability of the BFRP-RC shear wall is more in line with the requirement of recoverable functional aseismic structure in practical engineering.

It is often difficult to suppress vibration of flexible rotors at high-order critical speeds through conventional low-speed balancing, especially in the case of the rotor with initial bending. In this paper, a low-speed dynamic balancing method for flexible rotors with initial bending is presented first. Combining the modal information of the rotor with the measurement data at speeds below the critical speeds, the low-speed dynamic balancing method is able to balancing the critical speeds without directly measuring the vibrations at the critical speeds and the initial bending of the rotor. Based on this, a mode-by-mode forward higher-order-extra-trial-weight-free method is proposed for balancing the higher modes simultaneously. In the proposed method, the lower-mode balancing weights on different balancing planes are used as trial weights and linked by the modal ratios of the measuring points. This avoids the potential severe vibration when pass through the critical speeds if any additional trial weights are used for balancing the higher-order modes. The proposed method is validated by numerical simulation and experimental tests respectively. The results show that the proposed method is better than the traditional influence coefficient method in balancing performance. In addition, it also avoids potentially high resonant vibration response, thus providing a safer approach for the high order dynamic balancing of flexible rotors.

This study aims to investigate the life-cycle seismic performance degradation behaviour of reinforced concrete (RC) girder bridges under chloride-induced corrosion. Based on the Duracrete model and existing research results, the time-dependent deterioration models for the mechanical properties of longitudinal reinforcement, transverse reinforcement, cover concrete, and core concrete are determined. A three-span RC continuous girder bridge is taken as an example, and its nonlinear analysis models corresponding to different characteristic time points are established by the OpenSees platform. Four analysis cases are investigated to study the effects of chloride-induced corrosion on the girder bridge's seismic capacity and seismic demand. Among these cases, one involves the omission of considering the deterioration of ultimate tensile strain of reinforcing steel, while the remaining three consider this deterioration using three diverse degradation models. The results show that: in the presence of chloride-induced corrosion, the degradation of the ultimate tensile strain of reinforcing steel manifests markedly more severe than the deterioration observed in its yield strength; the girder bridge suffers a more significant decrease in ultimate curvature, a greater increase in curvature demand, and a lower curvature demand-to-capacity ratio of pier when considering the deterioration of ultimate tensile strain of reinforcing steel; disregarding the degradation of the ultimate tensile strain of reinforcing steel would render the life-cycle seismic performance evaluation results of girder bridge structures unreliable and unsafe; additionally, the applicability of these three deterioration models varies, and there are significant differences in the degree of degradation of curvature demand-to-capacity ratio among these models. Therefore, the choice among these three models should be grounded in the research application scenario. As a result, it is necessary to consider the deterioration characteristics of the ultimate tensile strain of reinforcing steel in the time-dependent seismic performance evaluation of RC girder bridges.

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.