振动抑制与能量俘获专刊序

工程系统中梁结构经常处于各种激励的作用下,因而梁结构在这种环境下不可避免地发生着各种各样的强迫振动.在梁结构发生振动的过程中,其自身会受到的温度、湿度、电磁场、裂纹等众多内外部因素的影响,而众多内外部因素就构成梁的多物理场耦合环境.在多场耦合环境下,Green函数法作为一种解析方法在研究梁的多场耦合振动问题方面具有优势,有利于讨论力、电、热、裂纹等因素作用下梁的振动特性和多场耦合特性.Green函数法相比于模态叠加法,优点在于能够得到完整且精度较高的解析解,具有收敛性好,运算快的特点.本文主要阐述Green函数在梁的强迫振动、热力耦合振动、力电耦合振动、裂纹梁振动等研究问题上取得了大量的理论和工程研究成果.本文以裂纹为内因,热、力、电为外因进行分类,阐述了在内外因影响下梁的强迫振动问题Green函数解的研究现状,从而让读者进一步系统性的了解Green函数法在振动领域中的广泛应用,以及了解该方法本身的特色和优势奠定基础.     

Event-triggered-based integral reinforcement learning output feedback optimal control for partially unknown constrained-input nonlinear systems

In this paper, an adaptive output feedback event-triggered optimal control algorithm is proposed for partially unknown constrained-input continuous-time nonlinear systems. First, a neural network observer is constructed to estimate unmeasurable state. Next, an event-triggered condition is established, and only when the event-triggered condition is violated will the event be triggered and the state be sampled. Then, an event-triggered-based synchronous integral reinforcement learning (ET-SIRL) control algorithm with critic-actor neural networks (NNs) architecture is proposed to solve the event-triggered Hamilton–Jacobi–Bellman equation under the established event-triggered condition. The critic and actor NNs are used to approximate cost function and optimal event-triggered optimal control law, respectively. Meanwhile, the event-triggered-based closed-loop system state and all the neural network weight estimation errors are uniformly ultimately bounded proved by Lyapunov stability theory, and there is no Zeno behavior. Finally, two numerical examples are presented to show the effectiveness of the proposed ET-SIRL control algorithm.     

Relation network based on multi-granular hypergraphs for person re-identification

Applied Intelligence - In recent years, person re-identification (re-ID) has become a widespread research topic that focuses on retrieving target pedestrians from a set of images, typically taken...     

Sandwiched Thin‐Film Anode of Chemically Bonded Black Phosphorus/Graphene Hybrid for Lithium‐Ion Battery

A facile vacuum filtration method is applied for the first time to construct sandwich‐structure anode. Two layers of graphene stacks sandwich a composite of black phosphorus (BP), which not only protect BP from quickly degenerating but also serve as current collector instead of copper foil. The BP composite, reduced graphene oxide coated on BP via chemical bonding, is simply synthesized by solvothermal reaction at 140 °C. The sandwiched film anode used for lithium‐ion battery exhibits reversible capacities of 1401 mAh g^?1 during the 200th cycle at current density of 100 mA g^?1 indicating superior cycle performance. Besides, this facile vacuum filtration method may also be available for other anode material with well dispersion in N‐methyl pyrrolidone (NMP).     

Silica shell-assisted synthetic route for mono-disperse persistent nanophosphors with enhanced in vivo recharged near-infrared persistent luminescence

Near-infrared (NIR) persistent-luminescence nanoparticles have emerged as a new class of background-free contrast agents that are promising for in vivo imaging.The next key roadblock is to establish a robust and controllable method for synthesizing monodisperse nanoparticles with high luminescence brightness and long persistent duration.Herein,we report a synthesis strategy involving the coating/etching of the SiO2 shell to obtain a new class of small NIR highly persistent luminescent ZnGa2O4∶Cr3+,Sn4+ (ZGOCS) nanoparticles.The optimized ZGOCS nanoparticles have an excellent size distribution of ～15 nm without any agglomeration and an NIR persistent luminescence that is enhanced by a factor of 13.5,owing to the key role of the SiO2 shell in preventing nanoparticle agglomeration after annealing.The ZGOCS nanoparticles have a signal-to-noise ratio ～3 times higher than that of previously reported ZnGa2O4∶Cr3+ (ZGC-1) nanoparticles as an NIR persistent-luminescence probe for in vivo bioimaging.Moreover,the persistent-luminescence signal from the ZGOCS nanoparticles can be repeatedly re-charged in situ with external excitation by a white lightemitting diode;thus,the nanoparticles are suitable for long-term in vivo imaging applications.Our study suggests an improved strategy for fabricating novel high-performance optical nanoparticles with good biocompatibility.     

A Change-Point Approach for Phase-I Analysis in Multivariate Profile Monitoring and Diagnosis

Process monitoring and fault diagnosis using profile data remains an important and challenging problem in statistical process control (SPC). Although the analysis of profile data has been extensively studied in the SPC literature, the challenges associated with monitoring and diagnosis of multichannel (multiple) nonlinear profiles are yet to be addressed. Motivated by an application in multioperation forging processes, we propose a new modeling, monitoring, and diagnosis framework for phase-I analysis of multichannel profiles. The proposed framework is developed under the assumption that different profile channels have similar structure so that we can gain strength by borrowing information from all channels. The multidimensional functional principal component analysis is incorporated into change-point models to construct monitoring statistics. Simulation results show that the proposed approach has good performance in identifying change-points in various situations compared with some existing methods. The codes for implementing the proposed procedure are available in the supplementary material.