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基于声信号时频特征的空间飞轮轴承状态识别方法

卞启龙 王虹 李雪晴 周宁宁 何田

上海航天(中英文)2024,Vol.41Issue(6):79-87,9.
上海航天(中英文)2024,Vol.41Issue(6):79-87,9.DOI:10.19328/j.cnki.2096-8655.2024.06.010

基于声信号时频特征的空间飞轮轴承状态识别方法

Spatial Flywheel Bearing State Recognition Method Based on Time-Frequency Characteristics of Acoustic Signals

卞启龙 1王虹 2李雪晴 3周宁宁 2何田1

作者信息

  • 1. 北京航空航天大学 交通科学与工程学院,北京 100191
  • 2. 北京控制工程研究所,北京 100094
  • 3. 北京飞机维修工程有限公司,北京 100624
  • 折叠

摘要

Abstract

Spatial flywheels have failed repeatedly due to the friction failures of their bearing cages,which affects the safe operation and life of spacecrafts in orbit.Therefore,it is very important to evaluate the frictional state of the bearing cage of a flywheel in its ground performance test.Since cages also have friction in normal operation,how to identify their health state under friction has become an urgent problem to be solved.In order to solve such a problem,this paper presents a spatial flywheel bearing state recognition method based on the time-frequency characteristics of acoustic signals.Firstly,the acoustic signals of a flywheel in its acceleration process are obtained by the ground test bench.Secondly,the three-dimensional(3D)waterfall diagram is used to identify the frictional types of the cage,and the high-energy frictional acoustic data radiated by the flywheel during the acceleration process are obtained.Thirdly,a time-frequency analysis is carried out on the high-energy frictional acoustic data to construct the characteristic parameters that can reflect the frictional stability of the flywheel.Finally,the entropy-weighting technique for order preference by similarity to an ideal solution(Topsis)is used to construct the comprehensive evaluation index.The application results of multiple flywheels show that the bearing health state recognition method proposed in this paper has high accuracy and can provide effective guidance for flywheel ground test and screening.

关键词

空间轴承/保持架摩擦/声信号/时频分析/健康状态识别

Key words

space bearing/cage friction/acoustic signal/time-frequency analysis/health status recognition

分类

机械制造

引用本文复制引用

卞启龙,王虹,李雪晴,周宁宁,何田..基于声信号时频特征的空间飞轮轴承状态识别方法[J].上海航天(中英文),2024,41(6):79-87,9.

基金项目

北京市重点实验室开放基金课题资助(BZ0388202201) (BZ0388202201)

上海航天(中英文)

OACSTPCD

2096-8655

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