An intelligent system for monitoring the microgravity environment quality on-board the international space station

被引：2

作者：

Lin, PP ^{[1
]}

Jules, K

机构：

[1] Cleveland State Univ, Dept Mech Engn, Cleveland, OH 44115 USA

[2] NASA, Glenn Res Ctr, Cleveland, OH 44135 USA

来源：

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT | 2002年 / 51卷 / 05期

关键词：

adaptive pattern recognition and classification; (APRC); back propagation neural network (BPNN); learning vector quantization (LVQ); microgravity; self-organizing feature map (SOFM); source detection; system monitoring;

D O I：

10.1109/TIM.2002.806016

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：1002 / 1009

页数：8