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倒频谱分析在滚动轴承故障诊断中的应用研究

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利用倒频谱分析对边频成分具有"概况"的能力,能方便提取、分析原频谱图上肉眼难以识别的周期信号,研究了倒频谱分析在滚动轴承故障诊断中的应用.对两组不同的滚动轴承内圈故障实验信号进行了分析,结果表明:若要利用倒频谱分析对滚动轴承进行有效的故障诊断,需要在信号采集时或者信号处理时降低背景噪声中较低频率的振动对采集信号的影响.
Research on Application of Cepstrum Analysis in Fault Diagnosis of Rolling Bearings
The use of cepstrum analysis has the"overview"ability for edge frequency components,which can easily extract and analyze the characteristics of periodic signals that are difficult to recognize by the naked eye on the original spectrum.The application of cepstrum analysis in rolling bearing fault diagnosis is discussed.By analyzing the experimental signals of two different sets of rolling bearing inner ring faults,the results show that in order to use cepstrum analysis for effective fault diagnosis of rolling bearings,it is necessary to reduce the impact of lower frequency vibrations in background noise on the collected signals during signal acquisition or signal processing.

rolling bearingfault diagnosisCepstrum

张斌

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山西工程职业学院 机械工程系,山西 太原 030009

滚动轴承 故障诊断 倒频谱

2022年度山西省高等学校科技创新项目

2022L709

2024

机械工程与自动化
山西省机电设计研究院 山西省机械工程学会

机械工程与自动化

影响因子:0.251
ISSN:1672-6413
年,卷(期):2024.(1)
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