摘要
微频差现象广泛存在于机械振动领域,为弥补频谱分析的不足,提出了2种识别微频差信号的时域方法。将2个、3个微频差时域信号绘制在笛卡尔坐标上,发现了对微频差较敏感的笛卡尔坐标特征。结合笛卡尔坐标特征,利用微分方法,进一步提出可用于识别多个微频差信号的累积特征,给出了多维空间下离散信号的累积算法,利用仿真计算说明了累积特征在识别微频差信号方面的有效性和敏感性。将笛卡尔坐标特征应用于转子轴心轨迹噪声来源分析,为轴心轨迹提纯提供了简单途径。将累积特征应用于叶片加工质量评价,为叶片质量控制提供新方法。工程应用表明,时域特征进行微频差信号识别是有效的。
As micro frequency difference phenomena exist in the field of mechanical vibration widely, two time do- main methods for identifying micro frequency difference are presented to compensate the shortcomings of spectral analysis. Two, three time domain signals with micro frequency difference are plotted in Cartesian coordinates respec- tively, and it is found that Cartesian coordinate characteristic is sensitive to micro frequency difference. Based on Cartesian coordinate characteristic and differential methods, an accumulation characteristic is proposed, which can be used to identify several micro frequency difference signals; and an accumulation algorithm is provided to deal with the discrete signals in multi-dimensional space. Simulation calculation shows the validity and sensitivity of accumula- tion characteristic in identifying micro frequency difference. Cartesian coordinate characteristic was applied in the analysis of the noises source of rotor axis track, which provides a simple means for the purification of rotor axis track. Accumulation characteristic was applied in the quality evaluation of blade processing, which provides a new method for blade quality control. Engineering applications show that time domain characteristic method is effective in micro frequency difference identification.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2012年第6期1234-1239,共6页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(50675099)资助项目
关键词
微频差
时域
笛卡尔坐标
累积
轴心轨迹
加工质量
micro frequency difference
time domain
Cartesian coordinate
accumulation
axis track
processing quality
