The integral grid-stiffened plate is often used as the outer wall structure of spacecraft, which can reduce weight and increase strength. The Lamb wave is often used to detect damage of plate structure due to its advantages of strong penetration and minimum attenuation over long distances. When the Lamb wave crosses the stiffeners, the dispersion, reflection, transmission and mode conversion waves will be superimposed, resulting in difficulties in damage detection and structural health monitoring (SHM). This paper proposed an improved total focusing method (TFM) to locate damage in integral grid-stiffened plates based on distributed piezoelectric wafer active sensors (PWAS) array. Firstly, the appropriate working frequency was selected to generate the A0 mode Lamb wave depending on the structure and sensors, and the full matrix capture (FMC) method was introduced to collect data. Secondly, TFM was used to obtain the initial imaging results and the possible area of damage can be assessed and identified. Thirdly, the double window functions were proposed to extract the scattering signal related to the damage for the specific mode (A0). Lastly, the TFM was used again to obtain the final imaging results and the damage can be correctly identified. The proposed method has been verified by three-dimensional finite element (FE) simulation as well as experiments. The experimental results show that the damage in an aluminum alloy integral grid-stiffened plate can be located with the error of 13mm.

A scheme of space self-organizing network based on TDMA (Time Division Multiple Access) is proposed for cooperative requirement in cluster flying micro-nano satellites. Network level, node level and process level models are created based on OPNET. Simulation experiments such as nodes autonomous networking, nodes autonomous joining, nodes autonomous exiting and network reorganizing are carried out and the key indexes such as networking time are tested. The scheme has been used in the cluster flying TianTuo-3 satellites developed by National Defense University of Science and Technology and on-orbit networking tests have been successfully carried out. This paper can provide a reference for the design and simulation of space self-organizing network.

In this paper, a generalized time-reversal-based imaging algorithm is presented and introduced into the area of ultrasonic Nondestructive evaluation (NDE) for imaging defect in solids. It can be expressed in different forms, including central frequency time-reversal with multiple signal classification (CF-TR-MUSIC), as well as its multi-frequency forms over a given frequency bandwidth, namely multi-frequency TR-MUSIC (MF-TR-MUSIC) and a related phase-coherent form (PC-MUSIC). These imaging algorithms are tested with experimental ultrasonic array data, and their performance is evaluated in terms of lateral resolution and sensitive to noise, two particularly important indicators for industrial NDE. It is shown that all three methods are capable of resolving lateral targets spaced closer than the Rayleigh limit, achieving super-resolution imaging. Both CF-TR-MUSIC and MF-TR-MUSIC can locate the positions of targets correctly, whereas the results from PC-MUSIC are less clear because of the presence of multiple peaks in the vicinity of target. However, an advantage of PC-MUSIC is that it can overcome the elongated point spread function that appears in TR-MUSIC images, and hence provide enhanced axial resolution. For high noise levels, MF-TR-MUSIC and PC-MUSIC are shown to provide stable image and suppress the presence of artifacts seen in the CF-TR-MUSIC image.