[1]汪 伟,李 军,翟旭升,等.某型航空发动机中介主轴承早期微弱故障诊断研究[J].机械与电子,2019,(06):6-10.
 ,,et al.Research on the Early Weak Fault Diagnosis of Aero-engine Intershaft Bearing[J].Machinery & Electronics,2019,(06):6-10.
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某型航空发动机中介主轴承早期微弱故障诊断研究()
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机械与电子[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2019年06期
页码:
6-10
栏目:
设计与研究
出版日期:
2019-06-24

文章信息/Info

Title:
Research on the Early Weak Fault Diagnosis of Aero-engine Intershaft Bearing
文章编号:
1001- 2257(2019)06- 0006- 05
作者:
汪 伟李 军翟旭升齐晨阳
空军工程大学航空机务士官学校,河南 信阳 436000
Author(s):
WANG WeiLIJunZHAIXushengQIChenyang
TheAviationMaintenanceNCO AcademyofAirForceEngineeringUniversity,Xinyang436000,China
关键词:
发动机中介主轴承故障诊断巴特沃斯滤波器微弱故障包络谱分析
Keywords:
aero- engineintershaftbearingfaultdiagnosisButterworthlow- passfilterweakfaultenvelopespectrumanalysis
分类号:
V231.92
文献标志码:
A
摘要:
针对基于机匣采集的振动信号难以有效提取出航空发动机中介主轴承早期微弱故障特征的问题,提出了基于巴特沃斯低通滤波器降噪和 Hilbert包络解调的中介主轴承早期微弱故障诊断方法。该方法依托带涡轮支承和外机匣的新型航空发动机中介主轴承试验器,首先,开展某型发动机巡航状态下健康中介主轴承试验,获取基准振动频谱特征;然后,进行外圈剥落预置故障的轴承试验,对采集的振动信号通过低通滤波降噪并进行 Hilbert包络分析解调出低频故障信号;最后,对比分析健康主轴承试验与轴承故障试验的时域波形、频谱和包络谱。结果表明,包络谱中转差信号与呈现“山”型边带特征,可用于诊断该型航空发动机中介主轴承外圈的早期剥落故障。
Abstract:
Anewanalysismethodcombinedwithleastmeansquare(LMS)algorithmandHilbertenvelopedemodulationwasproposedtosolvetheproblemofbeingdifficulttoextracttheweakfaultcharac
teristicsofaero engineerintershaftbearing,whichisbasedoncasingsignal.Firstly,theimpulseexperimentwasperformedbythehealthyintermediatebearing,thevibrationsignalsoftheoutercasingwasacquiredandanalyzed.Secondly,theexperimentoftherollingbearingwiththeouterracesfailurewasperformed,thefaultsignalwasextractedbylow passfilteringandHilbertenvelopedemodulation.Finally,frequencyspectrumandenvelopespectrumofthevibrationsignalbythefailurerollingbearingwerecomparedindetailwiththoseofthevibrationsignalsbythehealthyintermediatebearing.Theresultsdemonstratedthatthecharacteristicsoftheslipfrequencycombinedwiththeconvexshapesidebandfeature couldbeusedtodiagnosetheearlyspallingfaultofthemainbearingouterring.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019- 04- 03
作者简介:汪 伟 (1980-),男,湖北鄂州人,博士,讲师,研究方向为航空发动机故障预测与健康管理。
更新日期/Last Update: 2019-10-22