As the thermonuclear fuel container in inertial confinement fusion (ICF), the surface quality of the target capsule directly affects the success of ICF experiments. Therefore, it is crucial to inspect the morphology of ICF microspheres before fabrication. To address the issue of secondary damage to the surface of ICF microspheres during manipulation by current detection equipment, a bulk acoustic wave-driven microsphere manipulation device is proposed. This device excites an out-of-plane bending vibration mode in a vibrator composed of a piezoelectric ceramic and a metal substrate, creating an acoustic field within the liquid. The ICF microspheres are then driven by non-contact acoustic radiation forces, enabling non-destructive manipulation during ICF microsphere inspection. To analyze the relationship between the vibration of the manipulation device and the generated acoustic field, we developed an electromechanical coupling dynamics model of the vibrator using the transfer matrix method. This model comprehensively considers factors such as the size, material, boundary conditions, arrangement of piezoelectric ceramic sheets, excitation voltage, and additional load from water of the vibrator. Using this model, we calculated the vibration modes of a non-resonant traveling wave and two resonant standing waves, along with three corresponding acoustic fields. Based on calculation results, we fabricated and assembled the prototype. Vibration characteristics and manipulation performance of the prototype were studied through experiments. The results indicate a good agreement between theoretical calculations and experimental tests regarding the vibration characteristics of the acoustic manipulation device, validating the correctness of the established dynamics model. Both non-resonant traveling waves and resonant standing waves can effectively manipulate ICF microspheres, with the resonant standing wave achieving faster microsphere movement. This confirms the feasibility and effectiveness of the proposed acoustic manipulation method. Furthermore, based on the modal switching measurement and control method, the device can classify ICF microspheres by diameter without the need for a microscope.

To address the dynamics modeling of a single local damage fault in rolling bearings, a comprehensive approach based on Hertz contact theory has been developed.Specifically, a contact deformation retention factor is defined and a variable stiffness function using a static analysis method is proposed. This allowed us to establish and simulate a variable stiffness dynamics model for a single local damage fault in rolling bearings under radial load. The model was also experimentally validated. The research results show that when the rolling element enters the load zone its effective contact stiffness suddenly increases. Conversely, when it exits the load zone or falls into the fault position, the stiffness suddenly decreases. This change causes the contact force and contact deformation of other load-carrying rolling elements in the load zone to suddenly decrease or increase to rebalance the external load. However, this does not affect the effective contact stiffness of the rolling element itself. The effect is more pronounced for rolling elements near the center of the load zone. Additionally, these changes cause the total effective stiffness of the system to suddenly increase or decrease, leading to system vibrations. When the outer race has a fault, the change in total effective stiffness is of equal amplitude, resulting in an equal-amplitude time-domain vibration response. In contrast, when the inner race has a fault, both the change in total effective stiffness and the response amplitude are modulated by the rotation of the inner race, leading to significant variations. The proposed variable stiffness dynamics model is more consistent with reality and provides a certain theoretical basis for effective diagnosis of rolling bearing faults.

A nested Chebyshev polynomial surrogate model and an improved particle swarm optimization (IPSO) algorithm are proposed to identify the bounds of input and structural parameters in the inverse dynamical problem of flexible multibody systems with interval uncertainty. Specifically, the dynamical model equations for a multibody system incorporating interval uncertainty are established. The interval midpoint and interval radius are used to describe the given output response with interval uncertainty. The Chebyshev polynomial surrogate model is established for the output response of a flexible multibody system. The IPSO algorithm is used to reverse the interval midpoint and interval radius of the unknown parameters in the flexible multibody system. The Chebyshev polynomial surrogate model is used in the proposed method to approximate the original interval uncertain flexible multibody system, thereby significantly reducing the computational cost of the optimization process of the IPSO algorithm.

Ambient vibration energy harvesting technology can provide green self-powered supply technology for low-power electronic devices in the Internet of Things (IoTs). In response to the shortcomings of traditional linear cantilever beam energy harvesters with high natural frequencies and low energy capture efficiency, a tuning fork-shaped cantilever beam structure is proposed to collect vibration energy in the environment. This overcomes the disadvantage of traditional cantilever beam structures, where the free end section, due to its small strain during vibration, is not conducive to energy collection. As a result, the energy harvesting efficiency of the system is significantly enhanced. The Lagrange equation is used to establish the dynamic equation of a tuning fork piezoelectric cantilever beam under harmonic excitation. The influence of structure size, added tip-mass and load resistance on the energy capture characteristics of the system are analyzed through a combination of the theoretical analysis, finite element simulation (FEM) and experimental results. The results show that introducing a bifurcation structure at the free end of the cantilever beam can reduce the fundamental frequency of the system, proving that the tuning fork piezoelectric cantilever beam energy harvester is more conducive to low-frequency ambient vibration energy harvesting. When the acceleration excitation amplitude is 0.5 m/s², the peak output power of the system is 7 mW. Further optimization of the structure by adding a 20 g tip-mass at the free end increases the peak energy capture output power to 18 mW. Design a piezoelectric energy capture interface circuit to collect and convert electrical energy directly to power LED lights (light emitting diodes). Experimental results can simultaneously light up 50 LED lights. The research results can provide theoretical support for energy collection in low-frequency vibration environments and for achieving self-powered design of low-power IoT sensors below 80 Hz.

Flexible structures actuated by smart materials have been widely used in the fields of underwater bionic robotics, precision medical machines, micro/nano devices, and so on. It is still a challenging task to acquire the hydrodynamic force exerted on the oscillating flexible structure by the surrounding fluid. The fluid-structure coupled dynamic equation of the MFC-actuated flexible structure is established. A cantilever-based measurement system for the hydrodynamic force is proposed, and the performance indexes are also proposed. The characteristic parameters of the force measurement device are calibrated by experiments. Then, dynamic variations of the hydrodynamic forces exerted on the MFC-actuated flexible structure at different actuation levels are acquired using the proposed system. The measured hydrodynamic forces are decomposed into two components, namely, the added mass force and the hydrodynamic damping force. Moreover, the inertia and drag coefficients in the form of Morrison’s expression are obtained. Experimental results show that the underwater oscillating amplitude of the MFC-actuated structure increases from 3.67 mm to a maximum of 4.23 mm, as the excitation frequencies increase from 2.5 Hz to the resonant frequency of 3.1 Hz. Accordingly, the measured hydrodynamic force exerted on the oscillating structure increases significantly from 86.16 to 184.83 mN. However, the hydrodynamic force stays roughly unchanged, differing by no more than 15%. The proposed method and measurement system may be helpful for the design and application of the underwater flexible structure actuated by MFC and other smart materials.

The acoustic black hole (ABH) effect, which decelerates the propagation of elastic waves and suppresses boundary reflections, presents a novel mechanism for vibration energy harvesting. A dual-ABH piezoelectric beam energy harvester has been designed for application in railway track systems. A semi-analytical electromechanical coupling model was developed using the energy functional variational principle and Gaussian expansion method. Validation was conducted through finite element simulations. Under train-induced loading, energy harvesting behavior was investigated with respect to ABH geometric parameters and terminal mass. Four principal energy harvesting bands were identified within the 0~1500 Hz range, yielding a peak output voltage of 4.83 V and a maximum efficiency of 2.23%. Optimal energy conversion was achieved when the piezoelectric patch length equaled half the bending wave wavelength of the host structure. Efficiency was further improved by strengthening the ABH effect or through appropriate tuning of the terminal mass.

As the main component of the train body structure, the truss-cored flat panel is situated close to the wheel-track noise source and has a large area for noise radiation, and its acoustic performance directly influences the riding comfort of trains. This paper first establishes the wavenumber finite-element model and a sound-insulation prediction model for an aluminum truss-cored train floor using wavenumber finite elements and boundary integral equations. The wavenumber, transmission loss, and eigenvectors of the structure are calculated. The dispersion characteristics, sound-insulation performance and cross-sectional wave-modes of elastic waves are studied. The calculated results are compared with the prediction given in the references to verify the proposed model. Furthermore, this paper investigates the effects of the core layer's topological geometry of the extruded panel on the sound-insulation characteristics of aluminum extruded panels. The results show that varying the topological configuration of the core layer significantly changes the variation pattern of dispersion curves of elastic waves, which affects the sound-insulation properties of aluminum extruded panels. By comparing the topologies of classic extruded structures, it is found that the ‘herringbone’ ribbed plate structure has a relatively higher sound-insulation level and lower mass. This study can provide a reference for designing quiet and lightweight extruded panels.

To achieve high-precision prediction of bridge-coupled extreme stresses, the wavelet multi-resolution analysis method is adopted to decouple the coupled extreme stresses. The decoupled low-frequency data is taken as the trend item information, where the high-frequency data is considered as the vehicle load effect information. The trend item, after subtracting its mean, is the temperature load effect information. A bivariate Bayesian dynamic linear trend model (BDLTM), which introduces a time-varying trend term, is built to predict and analyze low-frequency extreme stress. GRU neural network model is provided to predict and analyze high-frequency extreme stresses. The dynamic coupled extreme stresses are predicted. The monitoring coupled data from Tianjin Fumin Bridge is provided to illustrate the feasibility and application of the proposed BDLTM-GRU model, the accuracy of which is compared with the single BDLTM model and single GRU model for verifying the high precision of the BDLTM-GRU model.

Adaptive decomposition, reconstruction, and denoising of bridge structure monitoring signals are critical parts in the research field of bridge health monitoring. To provide efficient and effective time-frequency domain denoising methods for these signals, an Adaptive Variational Mode Decomposition and Reconstruction (AVMDR) method was proposed for signal denoising, which can overcome the disadvantage of VMD (Variational Mode Decomposition) type methods that the number of decomposition components needs to be determined inadvance. The Empirical Mode Decomposition (EMD) method was introduced to adaptively determine the number of decomposition components, and then the Multi-scale Principal Component Analysis (MSPCA) was used to denoise each component and reconstruct the signal. The denoising performance of the proposed AVMDR method was validated and compared using both simulated signals—linear stationary and nonlinear non-stationary signals with varying noise levels—and real signals obtained from two cable-stayed model bridges. The results indicate that the AVMDR method outperforms other commonly used methods in terms of denoising performance, achieving optimal scores across all denoising performance evaluation metrics. Moreover, the AVMDR method can effectively retain more structural information while eliminating noise.

At present, the layout plan of cable force sensors for cable-stayed bridges usually selects different specifications of cables and cables with large cable forces or significant stress amplitude changes for monitoring, lacking a scientific method of cable force sensor placement. This study proposes an optimal cable force sensor placement method for long cable-stayed bridges based on sensitivity analysis, aiming to identify the structural damage in cable-stayed bridges. The proposed method is based on the sensitivity analysis of cable force to structural damage, and a genetic algorithm is used to obtain the minimum number and placement position of cable force sensors that required to identify structural damage in cable-stayed bridges. In addition, engineering experience and sensor placement habits are fully considered when determining the initial population and constraint condition of genetic algorithm. The proposed method is applied to the numerical model of the Yuxi River Bridge, and the optimal cable force sensor placement for cable-stayed bridges with the target of damage identification is realized. Moreover, the influence of sensitivity threshold on the optimal placement of sensors is discussed.