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
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
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.
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.