Ultrasonic pig for submarine oil pipeline corrosion inspection

1. Noel Duckworth, H., “Smart” Pigs Offer More Definitive Integrity Data, Pipe Line and Gas Industry, 2000.

2. Lauer, Gary and Moreno, Pam, New Pigs Combine Previously Separate Detection Technologies, Pipe Line and Gas Industry, 2001.

3. Liang, W., Que, P.W., Zhang, Q., and Yang, G., Ultrasonic Defect Detection of a Petroleum Pipeline in a Viscoelastic Medium, Russ. J. Nondestructive Testing, 2006, vol. 42, no. 10, pp. 692–699.

   Article  Google Scholar 

4. Song, S.P. and Que, P.W., Wavelet Based Noise Suppression Technique and Its Application to Ultrasonic Flaw Detection, Ultrasonics, 2006, vol. 44, pp. 188–193.

   Article  PubMed  Google Scholar 

5. Angrisani, L. and Daponte, P., Thin Thickness Measurements by Means of a Wavelet Transform-Based Method, Measurement, 1997, vol. 20, no. 4, pp. 227–242.

   Article  Google Scholar 

6. Margrave, F.W., Rigasb, K., Bradleyc, D.A., and Barrowcliffed, P., The Use of Neural Networks in Ultrasonic Flaw Detection, Measurement, 1999, vol. 25, pp. 143–154.

   Article  Google Scholar 

7. Legendre, S., Massicotte, D., Goyette, J., and Bose Tapan, K., Neural Classification of Lamb Wave Ultrasonic Weld Testing Signals using Wavelet Coefficients, IEEE Trans. Instrumentation and Measurement, 2001, vol. 50, no. 3, pp. 672–678.

   Article  Google Scholar 

8. Chen, T.L., Que, P.W., and Liu, Q.K., Pipeline Defects Diagnosis Based on Feature Extraction and Neural-Network Fusion, Russ. J. Nondestructive Testing, 2006, vol. 42, pp. 340–344.

   Article  CAS  Google Scholar 

9. Ruiz-Reyes, N., Vera-Candeas, P., Curpian-Alonso, J., Mata-Campos, R., and Cuevas-Martinez, J.C., New Matching Pursuit-Based Algorithm for SNR Improvement in Ultrasonic NDT, NDT E Int., 2005. vol. 38, pp. 453–458.

   Article  CAS  Google Scholar 

10. Dunlop, I. and McNab, A., Automated Parameter Extraction for Ultrasonic Flaw Analysis, IEE Proc. Sci. Meas. Technol., 1997, vol. 144, no. 2.

11. Yang, G., Zhang, Q., and Que, P.W., Matching-Pursuit-Based Adaptive Wavelet-Packet Atomic Decomposition Applied in Ultrasonic Inspection, Russ. J. Nondestructive Testing, 2007, vol. 43, pp. 62–68.

    Article  Google Scholar 

12. Dolgov, I.A., Gorchakov, V.A., Surkov, Yu.P., Rybalko, V.G., and Surkov, A.Yu., Assessing Changes in Stress-Corrosion Damageability on the Basis of Repeated in-Tube Nondestructive Testing, Russ. J. Nondestructive Testing, 2007, vol. 43, pp. 12–20.

    Article  Google Scholar 

13. Mao, Y.M. and Que, P.W., Noise Suppression and Flaw Detection of Ultrasonic Signals Via Empirical Mode Decomposition, Russ. J. Nondestructive Testing, 2007, vol. 43, pp. 196–203.

    Article  Google Scholar 

14. Gorchakov, V.A., Dolgov, I.A., Surkov, Y.P., et al., On the Analysis of In-Tube Flaw-Detection Results Characterizing the State of a Trunk Gas Pipeline with Corrosion Flaws, Russ. J. Nondestructive Testing, 2004, vol. 40, pp. 702–707.

    CAS  Google Scholar 

15. Reber, K., Beller, M., Willems, H., and Burbian, O.A., A New Generation of Ultrasonic In-Line Inspection Tools for Detecting, Sizing and Locating Metal Loss and Cracks in Transmission Pipelines, IEEE Ultrasonics Sysp., 2002, pp. 665–671.

16. Dolgov, I.A., Gorchakov, V.A., Pakhtusov, S.V., et al., Investigation of Behavior of Stress-Corrosion Cracks in a Pipes under Internal Pressure, Russ. J. Nondestructive Testing, 2002, vol. 38, pp. 143–148.

    Article  Google Scholar 

17. Zielinski, M., Chaberski, D., Kowalski, M., et al., High-Resolution Time-Interval Measuring System Implemented in Single FPGA Device, Measurement, 2004, vol. 35, pp. 311–317.

    Article  Google Scholar 

18. Schmidt, F., The SCSI Bus and IDE Interface Protocols, Application and Programming, Addison-Wesley Press, 1998.

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