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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

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空间飞轮多次由于轴承保持架摩擦故障导致失效,影响航天器的在轨安全运行和寿命.因此在飞轮地面性能测试中评估飞轮轴承保持架摩擦状态非常重要.由于保持架在正常运转中也有摩擦,如何辨识保持架摩擦情况下的健康状态成为一个亟须解决的问题.针对该问题,本文提出了一种基于时频特征的飞轮轴承保持架声诊断方法.首先,利用地面测试实验台获得飞轮升速过程中的噪声信号;其次,利用三维瀑布图对保持架摩擦类型进行鉴别,获得升速过程中飞轮辐射的大能量摩擦噪声数据;然后,对大能量摩擦噪声数据进行时频分析,构建可以反映飞轮摩擦稳定性的特征参数;最后使用熵权Topsis法构建综合评价指标.多个飞轮的应用结果表明:所提的轴承健康状态识别方法具有较高的准确率,可为飞轮地面测试和筛选提供有效指导.
Spatial Flywheel Bearing State Recognition Method Based on Time-Frequency Characteristics of Acoustic Signals
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.

space bearingcage frictionacoustic signaltime-frequency analysishealth status recognition

卞启龙、王虹、李雪晴、周宁宁、何田

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北京航空航天大学 交通科学与工程学院,北京 100191

北京控制工程研究所,北京 100094

北京飞机维修工程有限公司,北京 100624

空间轴承 保持架摩擦 声信号 时频分析 健康状态识别

2024

上海航天(中英文)
上海航天技术研究院

上海航天(中英文)

CSTPCD
影响因子:0.166
ISSN:2096-8655
年,卷(期):2024.41(6)