Sensors (Jan 2020)

An Impact Location Algorithm for Spacecraft Stiffened Structure Based on Posterior Possibility Correlation

  • Lei Qi,
  • Zhoumo Zeng,
  • Lichen Sun,
  • Xiaobo Rui,
  • Fan Fan,
  • Guixuan Yue,
  • Yueyang Zhao,
  • Hao Feng

DOI
https://doi.org/10.3390/s20020368
Journal volume & issue
Vol. 20, no. 2
p. 368

Abstract

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In order to ensure the safety of spacecrafts in orbit, impact location is an important part of structural health monitoring systems. In this paper, an impact location algorithm based on posterior probability correlation is proposed to solve the problem, that is, the impact point in the stiffened structure of a spacecraft is difficult to locate. The algorithm combines the Gaussian cross-correlation possibility weight method and the Bayesian posterior probability method. The cross-correlation possibility weight superposition based on grids was used to reduce the dependence of the accuracy of time difference extraction. Gaussian and normalized fitting were used to compensate the reflection, modal transformation, and amplitude attenuation of a stiffened plate. The location result was further optimized by the posterior probability. The proposed algorithm can be applied to the impact source localization of complex stiffened plate structures. The experiment results showed that the average location error can be 2.57 cm with proper sensor network schemes.

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