会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 10. 发明申请
    • METHOD AND APPARATUS FOR MONITORING AND ANALYZING VIBRATIONS IN ROTARY MACHINES
    • 用于监测和分析旋转机械振动的方法和装置
    • WO2010094915A1
    • 2010-08-26
    • PCT/GB2010/000281
    • 2010-02-17
    • OPTIMISED SYSTEMS AND SOLUTIONS LIMITEDTARASSENKO, LionelCLIFTON, DavidKING, DennisKING, StevenAULT, David
    • TARASSENKO, LionelCLIFTON, DavidKING, DennisKING, StevenAULT, David
    • G01H1/00
    • G01H1/006G01H3/08G01M13/028G01M13/045G01M15/12G01N29/46G01N2291/2693
    • A method of monitoring vibration amplitude and frequency in a rotary machine by spectral analysis of the vibration data. Vibration amplitudes are recorded as a function of rotation speed and of frequency and the data is analyzed to estimate a noise floor amplitude threshold for each of a plurality of different speed and frequency sub-ranges. Thus the noise floor varies for different speeds and frequencies. On the basis of training data known to be normal speed-frequency areas which contain significant spectral content in normal operation are deemed "known significant spectral content", so that during monitoring of new data points which correspond to significant vibration energy at speeds and frequencies different from the known significant spectral content can be deemed "novel significant spectral content" and form the basis for an alert. The estimation of the noise floor is based on a probabilistic analysis of the data in each speed-frequency area and from this analysis an extreme value distribution expressing the probability that any given sample is noise is obtained. For any new data sample the probability that it corresponds to noise can be read from this extreme value distribution, and an index calculated from this probability, with this technique being effective to detect higher order harmonics not usually detectable in vibration spectra.
    • 通过振动数据的频谱分析来监测旋转机械中振动振幅和频率的方法。 作为旋转速度和频率的函数记录振幅,并且分析数据以估计多个不同速度和频率子范围中的每一个的噪声基底振幅阈值。 因此,对于不同的速度和频率,本底噪声变化。 在已知正常速度频率区域的训练数据的基础上,将正常操作中含有重要频谱含量的速度频率区域视为“已知的有效频谱含量”,以便在监测对应于速度和频率下的显着振动能量的新数据点时 从已知的重要光谱内容可以被认为是“新的重要光谱内容”,并形成警报的基础。 噪声基底的估计基于每个速度 - 频率区域中的数据的概率分析,并且根据该分析,表示获得任何给定样本是噪声的概率的极值分布。 对于任何新的数据样本,可以从该极值分布中读取对应于噪声的概率,并从该概率中计算出一个指数,这种技术有效地检测振动频谱中通常不可检测到的高次谐波。