The precise detection of flaw echoes buried in backscattefing noise caused by material microstructure is a problem of great importance in uhrasonic non-destructive testing （NDT）. In this work, empirical mode decompo...The precise detection of flaw echoes buried in backscattefing noise caused by material microstructure is a problem of great importance in uhrasonic non-destructive testing （NDT）. In this work, empirical mode decomposition （EMD） is proposed to deal with ultrasonic signal. A time-frequency filtering method based on EMD is designed to suppress noise and enhance flaw signals. Simulated results are presented, showing that the proposed method has an excellent performance even for a very low signal-to-noise ratio （SNR）. The improvement in flaw detection was experimentally verified using stainless steel pipe sample with artificial flaws.展开更多
The accurate estimation of the rolling element bearing instantaneous rotational frequency(IRF) is the key capability of the order tracking method based on time-frequency analysis. The rolling element bearing IRF can b...The accurate estimation of the rolling element bearing instantaneous rotational frequency(IRF) is the key capability of the order tracking method based on time-frequency analysis. The rolling element bearing IRF can be accurately estimated according to the instantaneous fault characteristic frequency(IFCF). However, in an environment with a low signal-to-noise ratio(SNR), e.g., an incipient fault or function at a low speed, the signal contains strong background noise that seriously affects the effectiveness of the aforementioned method. An algorithm of signal preprocessing based on empirical mode decomposition(EMD) and wavelet shrinkage was proposed in this work. Compared with EMD denoising by the cross-correlation coefficient and kurtosis(CCK) criterion, the method of EMD soft-thresholding(ST) denoising can ensure the integrity of the signal, improve the SNR, and highlight fault features. The effectiveness of the algorithm for rolling element bearing IRF estimation by EMD ST denoising and the IFCF was validated by both simulated and experimental bearing vibration signals at a low SNR.展开更多
The randomly intermittent spectra (RIS) signal is employed to combat spectrum congestion in radar and other radio services to evade the external interferences in high-frequency (HF) and ultrahigh-frequency (UHF) bands...The randomly intermittent spectra (RIS) signal is employed to combat spectrum congestion in radar and other radio services to evade the external interferences in high-frequency (HF) and ultrahigh-frequency (UHF) bands. However, the spectra discontinuity of the signal gets rise to high range sidelobes when matching the reflected echo, which is much more difficult for targets detection. So it is indispensable to investigate the technique for sidelobes suppression of the range profile when RIS signal is utilized, This paper introduced a new processing technique based on time domain filtering to lower the range sidelobes. A robust and effetive algorithm is adopted to solve the coefficients of the filter, and the restriction on the desired response of the filter is derived. The simulation results show that the peak range sidelobe can be reduced to -27 dB from -9.5 dB while the frequency band span (FBS) is 200 kHz.展开更多
A time-frequency signal processing method for two-phase flow through a horizontal Venturi based on adaptive optimal-kernel （AOK） was presented in this paper.First,the collected dynamic differential pressure signal o...A time-frequency signal processing method for two-phase flow through a horizontal Venturi based on adaptive optimal-kernel （AOK） was presented in this paper.First,the collected dynamic differential pressure signal of gas-liquid two-phase flow was preprocessed,and then the AOK theory was used to analyze the dynamic differ-ential pressure signal.The mechanism of two-phase flow was discussed through the time-frequency spectrum.On the condition of steady water flow rate,with the increasing of gas flow rate,the flow pattern changes from bubbly flow to slug flow,then to plug flow,meanwhile,the energy distribution of signal fluctuations show significant change that energy transfer from 15-35 Hz band to 0-8 Hz band;moreover,when the flow pattern is slug flow,there are two wave peaks showed in the time-frequency spectrum.Finally,a number of characteristic variables were defined by using the time-frequency spectrum and the ridge of AOK.When the characteristic variables were visu-ally analyzed,the relationship between different combination of characteristic variables and flow patterns would be gotten.The results show that,this method can explain the law of flow in different flow patterns.And characteristic variables,defined by this method,can get a clear description of the flow information.This method provides a new way for the flow pattern identification,and the percentage of correct prediction is up to 91.11%.展开更多
In this paper, a detection technique for locating and determining the extent of defects and cracks in oil pipelines based on Hilbert-Huang time-frequency analysis is proposed. The ultrasonic signals reflected from def...In this paper, a detection technique for locating and determining the extent of defects and cracks in oil pipelines based on Hilbert-Huang time-frequency analysis is proposed. The ultrasonic signals reflected from defect-free pipelines and from pipelines with defects were processed using Hilbert-Huang transform, a recently developed signal processing technique based on direct extraction of the energy associated with the intrinsic time scales in the signal. Experimental results showed that the proposed method is feasible and can accurately and efficiently determine the location and size of defects in pipelines.展开更多
文摘The precise detection of flaw echoes buried in backscattefing noise caused by material microstructure is a problem of great importance in uhrasonic non-destructive testing （NDT）. In this work, empirical mode decomposition （EMD） is proposed to deal with ultrasonic signal. A time-frequency filtering method based on EMD is designed to suppress noise and enhance flaw signals. Simulated results are presented, showing that the proposed method has an excellent performance even for a very low signal-to-noise ratio （SNR）. The improvement in flaw detection was experimentally verified using stainless steel pipe sample with artificial flaws.
基金Project(51275030)supported by the National Natural Science Foundation of ChinaProject(2016JBM051)supported by the Fundamental Research Funds for the Central Universities,China
文摘The accurate estimation of the rolling element bearing instantaneous rotational frequency(IRF) is the key capability of the order tracking method based on time-frequency analysis. The rolling element bearing IRF can be accurately estimated according to the instantaneous fault characteristic frequency(IFCF). However, in an environment with a low signal-to-noise ratio(SNR), e.g., an incipient fault or function at a low speed, the signal contains strong background noise that seriously affects the effectiveness of the aforementioned method. An algorithm of signal preprocessing based on empirical mode decomposition(EMD) and wavelet shrinkage was proposed in this work. Compared with EMD denoising by the cross-correlation coefficient and kurtosis(CCK) criterion, the method of EMD soft-thresholding(ST) denoising can ensure the integrity of the signal, improve the SNR, and highlight fault features. The effectiveness of the algorithm for rolling element bearing IRF estimation by EMD ST denoising and the IFCF was validated by both simulated and experimental bearing vibration signals at a low SNR.
文摘The randomly intermittent spectra (RIS) signal is employed to combat spectrum congestion in radar and other radio services to evade the external interferences in high-frequency (HF) and ultrahigh-frequency (UHF) bands. However, the spectra discontinuity of the signal gets rise to high range sidelobes when matching the reflected echo, which is much more difficult for targets detection. So it is indispensable to investigate the technique for sidelobes suppression of the range profile when RIS signal is utilized, This paper introduced a new processing technique based on time domain filtering to lower the range sidelobes. A robust and effetive algorithm is adopted to solve the coefficients of the filter, and the restriction on the desired response of the filter is derived. The simulation results show that the peak range sidelobe can be reduced to -27 dB from -9.5 dB while the frequency band span (FBS) is 200 kHz.
基金Supported by the Natural Science Foundation of Zhejiang Province（Y1100842） the Planning Projects of General Administration of Quality Supervision Inspection and Quarantine of the People＇s Republic of China（2006QK23）
文摘A time-frequency signal processing method for two-phase flow through a horizontal Venturi based on adaptive optimal-kernel （AOK） was presented in this paper.First,the collected dynamic differential pressure signal of gas-liquid two-phase flow was preprocessed,and then the AOK theory was used to analyze the dynamic differ-ential pressure signal.The mechanism of two-phase flow was discussed through the time-frequency spectrum.On the condition of steady water flow rate,with the increasing of gas flow rate,the flow pattern changes from bubbly flow to slug flow,then to plug flow,meanwhile,the energy distribution of signal fluctuations show significant change that energy transfer from 15-35 Hz band to 0-8 Hz band;moreover,when the flow pattern is slug flow,there are two wave peaks showed in the time-frequency spectrum.Finally,a number of characteristic variables were defined by using the time-frequency spectrum and the ridge of AOK.When the characteristic variables were visu-ally analyzed,the relationship between different combination of characteristic variables and flow patterns would be gotten.The results show that,this method can explain the law of flow in different flow patterns.And characteristic variables,defined by this method,can get a clear description of the flow information.This method provides a new way for the flow pattern identification,and the percentage of correct prediction is up to 91.11%.
基金Project (No. 2001AA602021) supported by the Hi-Tech Researchand Development Program (863) of China
文摘In this paper, a detection technique for locating and determining the extent of defects and cracks in oil pipelines based on Hilbert-Huang time-frequency analysis is proposed. The ultrasonic signals reflected from defect-free pipelines and from pipelines with defects were processed using Hilbert-Huang transform, a recently developed signal processing technique based on direct extraction of the energy associated with the intrinsic time scales in the signal. Experimental results showed that the proposed method is feasible and can accurately and efficiently determine the location and size of defects in pipelines.
