To study the seismic performance of low-rise pavilion-type ancient timber structure, shaking table tests were conducted on a 1: 6 scaled model of the Xi’an Bell Tower. The Kobe wave, Lanzhou wave and Wenchuan wave with the seismic intensity levels ranging from 7-degree frequently to 9-rarely were considered as input excitations. The dynamic characteristics, dynamic responses and energy consumption of the structure were identified. The test results indicate that, as the peak ground acceleration(PGA) increased, the natural frequency of the model structure decreased marginally, while the damping ratio increased significantly. The stiffness was not uniformly distributed along the height of the structure, with the smallest stiffness found at the Dougong storey on the external gold cylinder, which also experienced the maximum inter-story drift. The acceleration amplification factors of the model were generally less than 1, exhibiting obvious seismic reduction effects. Compared with modern structures, the plastic strain energy of the ancient timber structure was relatively small, which helps reduce structural damage.

In the assembly process of an aero-turboshaft engine, the coaxiality errors of the curvic couplings are an important technical index, significantly affecting the performance and service life of the whole system. This study takes the turbine blade-casing of an aero-turboshaft engine as an example. The coaxiality errors (including both positional and orientation errors) of the curvic couplings are introduced into the clearance function of the blade tip-casing, the nonlinear dynamic model of a rotating taper-blade casing system is then proposed based on the Hamilton variational principle and the Galerkin method. The effectiveness of the proposed model is verified using ANSYS software. Two different acceleration functions are proposed: Function 1 assumes a constant acceleration value, while Function 2 adopts a cosine wave form for acceleration. The effects of different coaxiality errors of the curvic couplings on the transient response during both acceleration functions are further investigated using Newmark-β numerical method.Simulation results show that an increase in the coaxiality error of the curvic coupling leads to a reduction in the minimum clearance between the blade tip and casing, resulting in a more serious amplitude amplification induced by blade-tip casing rubbing. Compared with Function 1, Function 2 enables the system to pass through the critical speed more quickly, which advances the start time of rubbing. In addition, the maximum rubbing force and penetration depth can be effectively reduced due to the effects of the deceleration, weakening the rising and jumping phenomena in the system.

This study addresses the complex scenario where the parameters of the powertrain mounting system (PMS) of an electric vehicle exhibit both uncertainty and correlation. A robust design optimization method for the PMS, considering parametric uncertainty and correlation, is investigated. Firstly, based on Nataf transform and Monte Carlo sampling, the Nataf-Monte Carlo(NMC) method is proposed for the uncertainty and correlation analysis of PMS inherent characteristics, where the probabilistic parameters are correlated. Then, an efficient method, the Nataf-arbitrary polynomial chaos expansion (NAPCE) method, is derived for PMS response analysis by integrating Nataf transformation with arbitrary polynomial chaos expansion. Next, based on the NAPCE method and correlation coefficient weighting method, a robust design optimization method for PMS is developed, accounting for the uncertainty and correlation of responses. Finally, a numerical example is used to verify the effectiveness of the proposed method, and the robust optimization of the system is carried out. The results show that, compared to the NMC method, the NAPCE method offers good computational accuracy and efficiency for analyzing uncertainty and correlation in PMS responses. The proposed optimization method can configure the PMS parameters reasonably and improve the robustness of system.

Research on the identification and diagnosis of high-frequency friction signals under abnormal contact conditions of mechanical seals is limited. Therefore, a seal monitoring test-bed is established using high-frequency, wide-range, and highly sensitive acoustic emission (AE) technology. Acoustic emission signals are collected under various operating conditions of the mechanical seal, including start-stop, no pressure, low pressure, high pressure, low speed, and high speed. Then the collected data are processed and analyzed using time-domain, frequency-domain and time-frequency-domain analysis methods. A method for determining the interface friction state of the mechanical seal, based on the root mean square (RMS) change of the AE signal, is established. This method reveals the corresponding relationship between the end-face friction signal and the running state of the mechanical seal, from contact to non-contact, and further proves the seal operation process. The research identifies the evolution of the friction signal during the transition from boundary lubrication (BL) and mixed lubrication (ML) in end-face contact friction to sliding contact signals under non-contact hydrodynamic lubrication(HL). The frequency band of the AE signal during seal interface friction is found to be between 240 kHz and 320 kHz. Through time-frequency analysis of the AE signal, it is shown that continuous wavelet transform (CWT) effectively represents the time-frequency characteristics of the AE signal under different working conditions of the mechanical seal. The research results of this paper provide a theoretical foundation and data support for research on mechanical seal condition monitoring and fault diagnosis.

Tuned liquid damper (TLD) is a common type of passive damper system in high-rise buildingsl. However, the damping of a pure water TLD system is relatively small. Adding internal baffles can significantly increase its damping ratio, thereby improving its vibration control efficiency. In this study, a numerical simulation of liquid sloshing in a TLD system with vertical baffles is conducted using the open-source computational fluid dynamics(CFD) software OpenFOAM. The wind-induced response of the benchmark building for the third-generation wind-induced vibration control study is investigated using the computational structure dynamics (CSD) method. On this basis, the CFD/CSD coupling numerical simulation is conducted to evaluate the control efficiency on wind-induced vibration control of a tall building and a TLD system with built-in vertical baffles. The CFD/CSD coupling numerical simulation results show that the TLD system with three vertical baffles has a significant control effect on the wind-induced response of the benchmark building under dynamic wind loading with different return periods. The comparison with real-time hybrid test results also confirms that the proposed numerical algorithm in this paper has sufficient accuracy in estimating the wind-induced control efficiency.

A dynamic similitude design method is proposed for the problem of sudden unbalance of the rotor system. The dynamic differential equation requires the application of both equation analysis and dimensional analysis methods to establish the scaling laws, while also considering the damping scaling ratio. Based on the strain energy distribution criterion, a prototype rotor system is designed. The prototype is scaled according to the scaling laws to create a distorted model, and the dynamic similarity between the prototype and the distorted model is verified through simulation and test. The simulation results show that the distorted model exhibits high similarity to the prototype in terms of critical speed, strain energy distribution, and transient response. The errors for the first two critical speeds are 0.1% and 0.13%, respectively, and the error in peak amplitude is 3%. The test results show that the distorted model can accurately predict the critical speed and sudden unbalance vibration response of the prototype, with the errors for the first two critical speeds being 0.79% and 1.72%, respectively, and the error in peak amplitude being 5.98%.

Deep learning methods have shown great potential in the field of fault diagnosis of train wheelset bearings, but their effective implementation is based on the correct matching between various types of data and category labels. For data with a small number of label error samples, traditional deep learning methods are difficult to achieve the expected diagnostic effect. To address this issue, this paper proposes a fault diagnosis method combining box graph method and feature fusion model is proposed to address this issue. In this method, the outlier in each group of bearing signals is removed by box graph method, and the remaining data is expanded by the SMOTE method to restore to the original data size; Input the processed sample data into the improved feature fusion model for fault identification and classification. The experimental data of train wheel bearings was used for validation. The results showed that compared to directly using traditional neural network models for fault diagnosis, the diagnostic accuracy of the method proposed in this paper is higher, indicating that the method has better processing performance for bearing data with a small number of label error samples.

Capable of capturing offshore wind energy, the floating wind turbine is one of the primary research interests for researchers in the wind energy community. Researchers usually adopt two-dimensional low-degree-of-freedom simplified planar models for offshore barge-type wind turbines, where the model parameters are identified by the nonlinear least square method. In this case, the accuracy of these models depends highly on parameter fitting. Given the unique structure of offshore floating wind turbines and the surrounding environment, a multi-degree-of-freedom coupled dynamical model is necessary to yield more realistic dynamic behaviors. In this paper, we present a coupled dynamic model with 16 degrees of freedom for the multi-body system of barge-type offshore floating wind turbines under the combined action of wind and waves. The model accuracy is verified through numerical simulation using OpenFAST, developed by the National Renewable Energy Laboratory (NREL). In particular, the modified Blade Element Momentum theory is used to calculate the blade aerodynamic load, the linear potential flow theory is used to determine the wave load, and the quasi-static method is used to obtain the tension of the mooring systems. Besides the generator torque control and blade pitch control, a bi-directional tuned mass damper (TMD) is placed in the nacelle to mitigate the structural vibration of the floating wind turbine of the barge-type, where a limiting device is introduced to limit the TMD stroke. Subsequently, the control parameters are optimized by the method of exhaustion and the genetic algorithm. The simulation analyses show that the model proposed in this paper accurately alculates yields the dynamic response of the barge-type offshore floating wind turbine. The bi-directional TMD with collision mechanism is efficient in mitigating the structural response.

To investigate the influences of charge structures on the blast-induced ground vibration characteristics in hydraulic blasting, several onsite experiments were conducted in the context of Xinbin tunnel at the Shenyang to Jilin Expressway. Based on the onsite experiments, the peak particle velocity (PPV) and dominant frequency (DF) were analyzed under different kinds of charge structures, which includes the normal charge structure, the water bags located in the top of blasthole, the water bags located in the blasthole collar and the water bags located in the both ends of blasthole. In addition, the distribution laws of ground vibration under different charge structures were further studied using numerical simulation. The research results indicated that, compared with the normal charge structures, less explosive energy is converted into vibration energy in hydraulic blasting, resulting in smaller PPVs and higher DFs. Within 5 m of the cross section along the tunnel excavation face, the PPVs of blasting vibration under the normal charge structure exceed the vibration safety criteria, which is adverse for the safety control of ground structures. The converted vibration energy is relatively smaller along the direction of water bags in blasthole, but on the opposite direction of the blastholes more explosive energy is converted into vibration energy. In tunnel blasting excavation, the charge structure of the water bags located in the both ends of blasthole was recommended to promote the uniform distribution of vibration energy and minimize the disturbance to the surrounding structures.

Aiming at the complex mechanism and operation characteristics of the mechanical system of diesel engine on RO-RO passenger ship, a multi-component nonlinear vibration signal decomposition method and vibration characteristic parameter extraction strategy are proposed. The signal is decomposed into intrinsic mode function (IMF) components via empirical mode decomposition and restrained the end effects in empirical mode decomposition (EMD) by symmetrical extension. The sensitive component is extracted by the correlation. The characteristic frequencies are matched according to the amplitude demodulation spectrum via 4 order high energy operator (4th-HEO). The proposed method is illustrated by the three-dimensional vibration signals under 0 load and 100 load operation conditions of the RO-RO passenger ship. The results show that the analysis performance of vertical signals are better than other axial signals. And for the 9-cylinder 4-stroke diesel engine, the amplitudes of 0.5 times and 4.5 times are very prominent, and are more sensitive to load changes.