液体火箭发动机高速涡轮泵的振动故障检测

推进技术 ›› 1997, Vol. 18 ›› Issue (5): 13-16.

液体火箭发动机高速涡轮泵的振动故障检测

朱恒伟,黄卫东,王克昌,陈启智

国防科技大学航天技术系!长沙;410073;国防科技大学航天技术系!长沙;410073;国防科技大学航天技术系!长沙;410073;国防科技大学航天技术系!长沙;410073

发布日期:2021-08-15

FAULT DETECTION OF HIGH SPEED TURBOPUMP VIBRATION IN LIQUID PROPELLANT ROCKET ENGINE

Dept. of Aerospace Technology, National Univ. of Defence Technology, Changsha, 410073;Dept. of Aerospace Technology, National Univ. of Defence Technology, Changsha, 410073;Dept. of Aerospace Technology, National Univ. of Defence Technology, Changsha, 410073;Dept. of Aerospace Technology, National Univ. of Defence Technology, Changsha, 410073

Published:2021-08-15

摘要/Abstract

摘要： 讨论了涡轮泵故障的几个主要原因，据此提取涡轮泵振动数据的特征，用BP神经网络的方法进行故障检测。BP神经网络的训练样本集由一个具有无监督聚类功能的神经网络从原始的特征向量集获取。

关键词: 液体推进剂火箭发动机;涡轮泵;振动分析;人工神经元网络;故障分析

Abstract: Some main causes of occurred faults in the fuel trubopump of a rocket engine arediscussed. According to these faults, some features for fault detection are summarized from the powerspectrum density of a channel of vibration acceleration signal measured from the turbopump case.Neural networks are used to detect faults. With a BP neural network acting as fault detector, anunsupervised clustering neural network is used to obtain patterns required for training the faultdetector from the original test data characteristic vectors. The validation of the vibration signal inengine ground firing test shows the feasibility and effectiveness of this method.

Key words: Liquid propellant rocket engine;Turbine pump;Vibration analysis;Artificial neural network;Fault analysis

朱恒伟,黄卫东,王克昌,陈启智. 液体火箭发动机高速涡轮泵的振动故障检测[J]. 推进技术, 1997, 18(5): 13-16.