In this study,we report an analysis of cylinder head vibration signals at a steady engine speed using short-time Fourier transform(STFT).Three popular time-frequency analysis techniques,i.e.,STFT,analytic wavelet tran...In this study,we report an analysis of cylinder head vibration signals at a steady engine speed using short-time Fourier transform(STFT).Three popular time-frequency analysis techniques,i.e.,STFT,analytic wavelet transform(AWT) and S transform(ST),have been examined.AWT and ST are often applied in engine signal analyses.In particular,an AWT expression in terms of the quality factor Q and an analytical relationship between ST and AWT have been derived.The time-frequency resolution of a Gaussian function windowed STFT was studied via numerical simulation.Based on the simulation,the empirical limits for the lowest distinguishable frequency as well as the time and frequency resolutions were determined.These can provide insights for window width selection,spectrogram interpretation and artifact identification.Gaussian function windowed STFTs were applied to some cylinder head vibration signals.The spectrograms of the same signals from ST and AWT were also determined for comparison.The results indicate that the uniform resolution feature of STFT is not necessarily a disadvantage for time-frequency analysis of vibration signals when the engine is in stationary state because it can more accurately localize the frequency components excited by transient excitations without much loss of time resolution.展开更多
In this paper, we propose a method for characterizing a musical signal by extracting a set of harmonic descriptors reflecting the maximum information contained in this signal. We focus our study on a signal of orienta...In this paper, we propose a method for characterizing a musical signal by extracting a set of harmonic descriptors reflecting the maximum information contained in this signal. We focus our study on a signal of oriental music characterized by its richness in tone that can be extended to 1/4 tone, taking into account the frequency and time characteristics of this type of music. To do so, the original signal is slotted and analyzed on a window of short duration. This signal is viewed as the result of a combined modulation of amplitude and frequency. For this result, we apply short-term the non-stationary sinusoidal modeling technique. In each segment, the signal is represented by a set of sinusoids characterized by their intrinsic parameters: amplitudes, frequencies and phases. The modeling approach adopted is closely related to the slot window;therefore great importance is devoted to the study and the choice of the kind of the window and its width. It must be of variable length in order to get better results in the practical implementation of our method. For this purpose, evaluation tests were carried out by synthesizing the signal from the estimated parameters. Interesting results have been identified concerning the comparison of the synthesized signal with the original signal.展开更多
在微地震地面监测中,由于微地震信号能量微弱,因此很难对微地震事件进行精确拾取。本文提出了一种基于STA/LTA(short term averaging/long term averaging)的判别频率估计模式识别方法,可以避免由于设定阈值出现漏判小能量微地震事件的...在微地震地面监测中,由于微地震信号能量微弱,因此很难对微地震事件进行精确拾取。本文提出了一种基于STA/LTA(short term averaging/long term averaging)的判别频率估计模式识别方法,可以避免由于设定阈值出现漏判小能量微地震事件的情况,并在精度上比传统的STA/LTA方法提升10%以上。采用基于震幅叠加的能量聚焦方法对微地震事件进行定位计算,同时通过对能量聚焦结果的分析,进一步剔除"假"的微地震事件,从而能够更加精确地描述地下裂缝的发育情况。最后,通过对河北北部一水平井的压裂监测对该方法进行验证,结果表明,本方法计算效率高、监测结果获得施工单位的认可,能够对下一步压裂施工方案提供理论指导。展开更多
基金Project (No. 2011BAE22B05) supported by the National Key Technologies Supporting Program of China during the 12th Five-Year Plan Period
文摘In this study,we report an analysis of cylinder head vibration signals at a steady engine speed using short-time Fourier transform(STFT).Three popular time-frequency analysis techniques,i.e.,STFT,analytic wavelet transform(AWT) and S transform(ST),have been examined.AWT and ST are often applied in engine signal analyses.In particular,an AWT expression in terms of the quality factor Q and an analytical relationship between ST and AWT have been derived.The time-frequency resolution of a Gaussian function windowed STFT was studied via numerical simulation.Based on the simulation,the empirical limits for the lowest distinguishable frequency as well as the time and frequency resolutions were determined.These can provide insights for window width selection,spectrogram interpretation and artifact identification.Gaussian function windowed STFTs were applied to some cylinder head vibration signals.The spectrograms of the same signals from ST and AWT were also determined for comparison.The results indicate that the uniform resolution feature of STFT is not necessarily a disadvantage for time-frequency analysis of vibration signals when the engine is in stationary state because it can more accurately localize the frequency components excited by transient excitations without much loss of time resolution.
文摘In this paper, we propose a method for characterizing a musical signal by extracting a set of harmonic descriptors reflecting the maximum information contained in this signal. We focus our study on a signal of oriental music characterized by its richness in tone that can be extended to 1/4 tone, taking into account the frequency and time characteristics of this type of music. To do so, the original signal is slotted and analyzed on a window of short duration. This signal is viewed as the result of a combined modulation of amplitude and frequency. For this result, we apply short-term the non-stationary sinusoidal modeling technique. In each segment, the signal is represented by a set of sinusoids characterized by their intrinsic parameters: amplitudes, frequencies and phases. The modeling approach adopted is closely related to the slot window;therefore great importance is devoted to the study and the choice of the kind of the window and its width. It must be of variable length in order to get better results in the practical implementation of our method. For this purpose, evaluation tests were carried out by synthesizing the signal from the estimated parameters. Interesting results have been identified concerning the comparison of the synthesized signal with the original signal.
文摘在微地震地面监测中,由于微地震信号能量微弱,因此很难对微地震事件进行精确拾取。本文提出了一种基于STA/LTA(short term averaging/long term averaging)的判别频率估计模式识别方法,可以避免由于设定阈值出现漏判小能量微地震事件的情况,并在精度上比传统的STA/LTA方法提升10%以上。采用基于震幅叠加的能量聚焦方法对微地震事件进行定位计算,同时通过对能量聚焦结果的分析,进一步剔除"假"的微地震事件,从而能够更加精确地描述地下裂缝的发育情况。最后,通过对河北北部一水平井的压裂监测对该方法进行验证,结果表明,本方法计算效率高、监测结果获得施工单位的认可,能够对下一步压裂施工方案提供理论指导。
