Title :
An intelligent system for monitoring the microgravity environment quality on-board the International Space Station
Author :
Lin, Paul P. ; Jules, Kenol
Author_Institution :
Mech. Eng. Dept., Cleveland State Univ., OH, USA
fDate :
10/1/2002 12:00:00 AM
Abstract :
An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen´s self-organizing feature map, learning vector quantization, and a back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system.
Keywords :
aerospace instrumentation; backpropagation; fuzzy logic; learning (artificial intelligence); pattern recognition; self-organising feature maps; space vehicles; vector quantisation; zero gravity experiments; International Space Station; back propagation neural network; fuzzy logic; intelligent system; known patterns; learning vector quantization; microgravity environment quality; self-organizing feature map; unknown patterns; vibrating source activation; Acceleration; Data analysis; Frequency; Intelligent systems; International Space Station; Monitoring; Neural networks; Pattern recognition; Space shuttles; Vector quantization;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2002.806016
