The growing use of composite structures in aerospace structures has attracted much interest in structural health monitoring (SHM) for the localization of impact positions due to their poor impact resistance properties. The propagation mechanism and the frequency dispersion features of signals on complex composite structures are more complicated than those on simple composite plates. In this paper, a time reversal focusing based impact imaging method for impact localization of complex composite structures is proposed. A complex Shannon wavelet transform is adopted to extract frequency narrow-band signals of impact response signals of a PZT sensors array at a special time-frequency scale and to measure the phase velocity of the signals. The frequency narrow-band signals are synthesized using software, depending on the time reversal focusing principle, to generate an impact image to estimate the impact position. A demonstration system is built on a composite panel with many bolt holes and stiffeners on an aircraft wing box to validate this method. The validating results show that the method can estimate the position of impact efficiently.

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Lamb waves are widely used in structural health monitoring (SHM) of plate-like structures. Due to the dispersion effect, Lamb wavepackets will be elongated and the resolution for damage identification will be strongly affected. This effect can be automatically compensated by the time reversal process (TRP). However, the time information of the compensated waves is also removed at the same time. To improve the spatial resolution of Lamb wave detection, virtual time reversal (VTR) is presented in this paper. In VTR, a changing-element excitation and reception mechanism (CERM) rather than the traditional fixed excitation and reception mechanism (FERM) is adopted for time information conservation. Furthermore, the complicated TRP procedure is replaced by simple signal operations which can make savings in the hardware cost for recording and generating the time-reversed Lamb waves. After the effects of VTR for dispersive damage scattered signals are theoretically analyzed, the realization of VTR involving the acquisition of the transfer functions of damage detecting paths under step pulse excitation is discussed. Then, a VTR-based imaging method is developed to improve the spatial resolution of the delay-and-sum imaging with a sparse piezoelectric (PZT) wafer array. Experimental validation indicates that the damage scattered wavepackets of A 0 mode in an aluminum plate are partly recompressed and focalized with their time information preserved by VTR. Both the single damage and the dual adjacent damages in the plate can be clearly displayed with high spatial resolution by the proposed VTR-based imaging method.

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This paper presents a new parallel distributed structural health monitoring technology based on the wireless sensor network and multi-agent system for large scale engineering structures. The basic idea of this new technology is that of adopting the smart wireless sensor with on-board microprocessor to form the monitoring sensor network and the multi-agent technology to manage the whole health monitoring system. Using this technology, the health monitoring system becomes a distributing parallel system instead of a serial system with all processing work done by the central computer. The functions, the reliability, the flexibility and the speed of the whole system will be greatly improved. In addition, with wireless communication links instead of wires, the system weight and complexity will be lowered. In this paper, the distributed smart wireless sensor network is designed first based on the Berkeley Mote Mica wireless sensor platform. Two kinds of sensor have been adopted: piezoelectric sensors and electric resistance wires. They are connected to a Mica MPR board though a designed charge amplifier circuit or bridge circuit and MTS101 board. Seven kinds of agents are defined for the structural health monitoring system. A distributed health monitoring architecture based on the defined agents is proposed. Finally, a composite structural health monitoring system based on a Mica wireless platform and multi-agent technology is developed to evaluate the efficacy of the new technology. The developed system can successfully monitor the concentrated load position or a loose bolt position.

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Background: Chondrogenic progenitor cells (CPCs) have high self-renewal capacity and chondrogenic potential. Intra-articular delivery of purified mesenchymal stem cells (MSCs) from MRL/MpJ "superhealer" mice increased bone volume during repair and prevents post-traumatic arthritis. Recently, although extracellular vesicles released from MSCs have been used widely for treating OA, the application of extracellular vesicles secreted by CPCs from MRL/ MpJ mice in OA therapy has never been reported. In this study, we evaluated the effects of extracellular vesicles secreted by CPCs from control CBA (CBA-EVs) and MRL/MpJ mice (MRL-EVs) on proliferation and migration of murine chondrocytes. We also determined here if weekly intra-articular injections of CBA-EVs and MRL-EVs would repair and regenerate surgically induced model in mice. Methods: CPC surface markers were detected by flow cytometry. CBA-EVs and MRL-EVs were isolated using an ultrafiltration method. Nanoparticle tracking analysis, transmission electron microscopy, and western blots were used to identify extracellular vesicles. CBA-EVs and MRL-EVs were injected intra-articularly in a mouse model of surgical destabilization of the medial meniscus (DMM)-induced OA, and histological and immunohistochemistry analyses were used to assess the efficacy of exosome injections. We used miRNA-seq analysis to analyze the expression profiles of exosomal miRNAs derived from CBA-EVs as well as MRL-EVs. Cell-counting and scratch assays were used to evaluate the effects of CBA-EVs and MRL-EVs on proliferation and migration of murine chondrocytes, respectively. Meanwhile, a specific RNA inhibitor assesses the roles of the candidate miRNAs in CPC-EV-induced regulation of function of chondrocytes.