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Proceedings Article

Adaptive sensor array algorithm for structural health monitoring of helmet

[+] Author Affiliations
Xiaotian Zou, Ye Tian, Nan Wu, Kai Sun, Xingwei Wang

Univ. of Massachusetts Lowell (USA)

Proc. SPIE 7984, Health Monitoring of Structural and Biological Systems 2011, 79841A (March 31, 2011); doi:10.1117/12.880509
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From Conference Volume 7984

  • Health Monitoring of Structural and Biological Systems 2011
  • Tribikram Kundu
  • San Diego, California, USA | March 06, 2011

abstract

The adaptive neural network is a standard technique used in nonlinear system estimation and learning applications for dynamic models. In this paper, we introduced an adaptive sensor fusion algorithm for a helmet structure health monitoring system. The helmet structure health monitoring system is used to study the effects of ballistic/blast events on the helmet and human skull. Installed inside the helmet system, there is an optical fiber pressure sensors array. After implementing the adaptive estimation algorithm into helmet system, a dynamic model for the sensor array has been developed. The dynamic response characteristics of the sensor network are estimated from the pressure data by applying an adaptive control algorithm using artificial neural network. With the estimated parameters and position data from the dynamic model, the pressure distribution of the whole helmet can be calculated following the Bazier Surface interpolation method. The distribution pattern inside the helmet will be very helpful for improving helmet design to provide better protection to soldiers from head injuries.

© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Xiaotian Zou ; Ye Tian ; Nan Wu ; Kai Sun and Xingwei Wang
"Adaptive sensor array algorithm for structural health monitoring of helmet", Proc. SPIE 7984, Health Monitoring of Structural and Biological Systems 2011, 79841A (March 31, 2011); doi:10.1117/12.880509; http://dx.doi.org/10.1117/12.880509


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