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harmonic wavelet analysis
相关语句
  谐波小波分析
     HARMONIC WAVELET ANALYSIS OF SINGULAR SIGNAL
     奇异信号的谐波小波分析
短句来源
     HARMONIC WAVELET ANALYSIS OF CHAOS AND NOISE SIGNAL
     混沌与噪声信号的谐波小波分析
短句来源
     FAULT DIAGNOSIS METHOD BASED ON HARMONIC WAVELET ANALYSIS
     基于谐波小波分析的故障诊断方法研究
短句来源
     Harmonic Wavelet Analysis and Its Application to Analyzing Signals of Rotating Machinery
     谐波小波分析及其在旋转机械信号分析中的应用
短句来源
     Harmonic wavelet analysis can extract the singular components in the non-stationary signal effectively.
     谐波小波分析可有效提取非平稳信号中的奇异成分。
短句来源
更多       
  谐小波分析
     Since faults of rotating machinery appear in a complicated manner, a method called the harmonic wavelet fuzzy neural network method ,which is a combination of harmonic wavelet analysis, fuzzy theory and neural networks is being presented.
     根据旋转机械复杂的故障特点,提出了结合谐小波分析、模糊理论和神经网络形成的谐小波模糊神经网络方法,并将其应用于旋转机械的故障诊断,实现了模糊故障诊断。
短句来源
  谐波小波
     Torsional Vibration Inherent Frequencies Extraction Based on AR Model and Harmonic Wavelet Analysis
     基于AR模型和谐波小波的扭振固有频率提取
短句来源
     HARMONIC WAVELET ANALYSIS OF SINGULAR SIGNAL
     奇异信号的谐波小波分析
短句来源
     HARMONIC WAVELET ANALYSIS OF CHAOS AND NOISE SIGNAL
     混沌与噪声信号的谐波小波分析
短句来源
     FAULT DIAGNOSIS METHOD BASED ON HARMONIC WAVELET ANALYSIS
     基于谐波小波分析的故障诊断方法研究
短句来源
     Harmonic Wavelet Analysis and Its Application to Analyzing Signals of Rotating Machinery
     谐波小波分析及其在旋转机械信号分析中的应用
短句来源
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This paper introduces key technologies on dynamic analysis and monitoring-diagnosis of varying operation and nonstationarity, which are suitable for large mechanical equipment under on-line and off-line conditions. They are frequency band energy monitoring via wavelet packets, spectral analysis of wavelet-autoregressive, harmonic wavelet analysis, wavelet fractal analysis, generalized adaptive wavelet analysis, fuzzy identification using principal component and autoregressive spectrum,...

This paper introduces key technologies on dynamic analysis and monitoring-diagnosis of varying operation and nonstationarity, which are suitable for large mechanical equipment under on-line and off-line conditions. They are frequency band energy monitoring via wavelet packets, spectral analysis of wavelet-autoregressive, harmonic wavelet analysis, wavelet fractal analysis, generalized adaptive wavelet analysis, fuzzy identification using principal component and autoregressive spectrum, fuzzy cluster neural network based on wavelet packets, monitoring- diagnosis device and systems for mechanical equipment etc. Engineering applications are illustrated with examples. Mechanical faults like looseness, surge, bearing defect, friction, misalignment, unbalance and so on were diagnosed successfully.

介绍适用于大型机械设备变工况非平稳在线和离线动态分析与监测诊断的关键技术:小波包频带能量监测、小波包自回归谱分析、谐波小波分析、小波分形分析、广义自适应小波分析、主分量自回归谱模糊识别、小波包模糊聚类网络分类、机械设备监测诊断装置与系统等。举例说明了这些技术在工程中的应用,成功地诊断出松动、喘振、轴承缺陷、摩擦、不对中、失衡等多种机械故障。

Harmonic wavelet definition and characteristics are introduced. In harmonic wavelet analysis, wavelet time frequency map and contour plot are ususlly used to show the harmonic wavelet decompositon. They can illustrate the distribution of signal energy over time frequency directly, furthermore, identify weak singularity in a pure signal clearly. When the signal possesses noise, these two methods become ineffective on identifying singularity, so they are almost useless in practice. A...

Harmonic wavelet definition and characteristics are introduced. In harmonic wavelet analysis, wavelet time frequency map and contour plot are ususlly used to show the harmonic wavelet decompositon. They can illustrate the distribution of signal energy over time frequency directly, furthermore, identify weak singularity in a pure signal clearly. When the signal possesses noise, these two methods become ineffective on identifying singularity, so they are almost useless in practice. A new method, wavelet time frequency profile plot (TFPP) is proposed, which can suppress the effect of noise and recognise weak singularity. With TFPP, vibration data of a key rotating machine in an oil refinery are analysed. After synthesizing fast Fourier transform, singular feature of the signal is extracted and weak fault is diagnosed successfully.

分析了谐波小波的定义、特点 ,以及用谐波小波时频图、等高线图表示谐波小波分解结果的方法 .分析结果表明 ,这两种方法虽然可以直观表示信号的时频能量分布以及无噪声信号中的微弱奇异成分 ,但当信号中存在噪声时 ,用这些方法将难以检测信号的奇异性 ,因而它们在工程实际中几乎是没有用的 .提出了谐波小波时频剖面图 (Time FrequencyProfilePlot,即TFPP)方法 ,利用该方法可以检测含噪声信号的微弱奇异成分 .运用谐波小波时频剖面图方法分析了某炼油厂关键旋转机械的振动数据 ,综合快速傅里叶转换 ,有效地提取了信号的微弱奇异特征 ,并诊断了系统故障 .

Harmonic wavelet analysis and its filter method is introdaced.We use this method to analyze the vibration signals of a rotor system,to abstract the features of the signals and identify the critical speed of the rotor.Practice shows that this method and its results are practically valuable.

介绍了谐波小波分析及其滤波方法 ,并运用该方法对转子系统振动信号进行分析 ,提取信号特征 ,识别转子临界转速。实践表明 ,该识别方法具有较大的工程实用价值

 
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