Spacecraft Segment Damage Identification Method Based on Fiber Optic Strain Difference Field Reconstruction and Norm Calculation

Abstract

Real-time online identification of spacecraft segment damage is of great significance for realizing spacecraft structural health monitoring and life prediction. In this paper, a damage response characteristic field inversion algorithm based on the differential reconstruction of strain response is proposed to solve the problem of not being able to recognize the small damages of spacecraft structure directly by the strain response alone. Four crack damage location identification methods based on vector norm computation are proposed, which realize online identification and precise location of structural damage events without external excitation by means of spacecraft structural working loads only. A spacecraft segment structural damage monitoring system based on fiber optic grating sensors was constructed, and the average error of damage localization based on the curvature vector 2 norm calculation was 2.58 mm, and the root-mean-square error was 1.98 mm. The results show that the method has superior engineering applicability for on-orbit service environments.

Some Considerations about the Incorporation of Dynamic Parameters in the Structural Health Monitoring Systems of Bridges

“…In order to have a greater knowledge of the structure to be studied and to allow the adequate implementation of an SHM system, the advantages of having continuous instrumentation compared to a discontinuous one are clear [4][5][6][7]. Furthermore, as indicated in the introduction, new technologies offer great possibilities that have yet to be explored [8][9][10][11][12][13][14].…”

“…Regarding the introduction of new technologies in SHM systems, the current panorama is in continuous evolution and fields of work that until now were unthinkable are opening. Thus, for example, a number of recent publications may be mentioned: Han et al about the introduction of nanosensors [8]; Dong, Bas, and Catbas or Bai et al in relation to the use of systems based on computer vision to monitor the behaviour of bridges, even long spans [9,10]; Xu et al on the methodology for identifying damage in spacecraft from measurements made on optical fibre [11]; Ramón-Zamora et al in the field of evaluation of reinforcement corrosion in concrete structures by means of embedded sensors [12]; Jia and Li on the introduction of tools based on deep learning [13]; and Biondi et al on the application of synthetic aperture radars [14].…”

Yoke-Type Elasto-Magnetic Sensor-Based Tension Force Monitoring Method for Enhancement of Field Applicability

“…Moreover, in recent years, tension material monitoring research has expanded to other fields, such as aerospace, mooring lines in subsea structures, and nuclear containment building. Research has been conducted on building a structural health monitoring system for spacecraft segments based on fiber optic sensors and the calculation of the strain response difference characteristics [ 9 ]. Studies have been conducted on the dynamic instability behavior of suspended floating tunnel (SFT) using fluid, structural, and dynamic analysis techniques [ 10 ] and also on the development of offshore structural health monitoring using fiber bragg grating (FBG) sensors [ 11 ].…”