|Table of Contents|

Clustering analysis for fault data in steady process of liquid propellant rocket engine(PDF)

《火箭推进》[ISSN:1672-9374/CN:CN 61-1436/V]

Issue:
2015年02期
Page:
118-122
Research Field:
测控与试验
Publishing date:

Info

Title:
Clustering analysis for fault data in steady process of liquid propellant rocket engine
Author(s):
ZHANG Xiang;  XU Hong-ping;  AN Xue-yan;  GENG Hui;  ZHANG Su-ming
Beijing Institute of Space System Engineering, Beijing 100076, China
Keywords:
liquid propellant rocket engineIMScluster analysis
PACS:
V434-34
DOI:
-
Abstract:
As a branch of statistics, clustering analysis has been widely studied for many years, and formed a system of the systematic method. The data mining based on clustering analysis method has achieved a good effect in practice. IMS algorithm presented by NASA according to the development of the intelligent monitoring system and fault diagnosis technology is a real-time monitoring algorithm to use normal database to monitor the abnormal data, which has been used by NASA in many aspects and gained a satisfactory effect. The included angle cosine IMS clustering analysis method based on steady process fault data of LRE is proposed in this article on the basis of analysis of the IMS algorithm of SSME. It was verified by simulation analysis.

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