摘要：Monitoring pipeline wall is an important issue in oil and gas industries. Over time, the defect can occur in the pipeline and can impact surrounding population, environment and may result in injuries or fatalities. While flaws in the pipeline could be detected by ultrasonic testing and monitoring the severity of the flaw. The limitation of ultrasonic testing is the signal contaminate with backscattering noise, which masks flaw echoes in the measured signal. Signal processing take place in the recent year to de-noising for improving signal-to-noise ratio and extract the feature for flaws classification. This paper presents a comprehensive overview of signal processing techniques used to improve ultrasonic detection method with and without intelligent classifier. Finally, the advantages and disadvantages feature extraction provided for classifications process.
