10.14489/td.2016.08.pp.030-033

2016, 08 August

DOI: 10.14489/td.2016.08.pp.030-033

Slesarev D.A., Belaia A.V.
AUTOMATED CLASSIFICATION OF PIPELINE STRUCTURAL COMPONENTS ON THE BASE MFL IN-LINE INSPECTION
(pp. 30-33)

Abstract. The article is devoted to the problem of pipeline structural components identification. This is an actual problem because, on the one hand, structural components can act as reference marks for verification of defect location, on the other hand, structural components cause often false calls. Typical C-scan of such components as pipebends, T-bends and sliding valves is shown on figures. A set of morfometrical image features and standard signal features are proposed as a basis for structural component identification from MFL in-line inspection data. Statistical discriminant method is used to identify pipe-bends, T-bends and sliding valves. Proposed algorithm has applied to test data from MFL inspection of two short pipeline branches made by means of VID219 MFL instrument. The Algorithm has given correct classification results.

Keywords: in-line pipeline diagnostics, MFL non-destructive testing, image recognition, signal processing.

+ - About the Authors Click to collapse

D. A. Slesarev (INTRON PLUS, Moscow, Russia)
A. B. Belaia (INTRON VTD, Moscow, Russia)

+ - References Click to collapse

1. Slesarev D. A., Vasin E. S., Stepanov N. O. et al. (2005). Identification and assessment of defects parameters in magnetic in-line inspection using MDScan defectoscope. Proceedings of the XVII Russian scientific and technical conference «Nondestructive testing and diagnostics». (p. 327). Ekaterinburg. [in Russian language]
2. Slesarev D. A., Abakumov A. A. (2013). Data processing and representation in the MFL method for nondestructive testing. Defektoskopiia, (9), pp. 3 – 9. [in Russian language]
3. Reber K., Willems H., Barbian A.O. et al. (2004). Application of artificial intelligence for the analysis of data acquired by in-line inspection of pipelines. WCNDT 2004.
4. Fasteners. Main Parameters. (1986). Ru Standard No. GOST 9698–86. USSR. Moscow. [in Russian language]
5. Standard and transitional pipe wyes. Ru Standard No. GOST 17376–2001. Russian Federation. Moscow. [in Russian language]
6. Short radius bends. Ru Standard No. GOST 17375–83. USSR. Moscow. [in Russian language]
7. Barat V., Lunin V., Seidel H.-U., Bock A. (2003). Signal processing of magnetic flux leakage data obtained from pipeline inspection. 48th Intern. Scientific Colloquium: Proceedings Ilmenau, Germany, pp. 131-132.
8. Pratt E. (1982). Digital image processing. Moscow: Mir. [in Russian language]
9. Nosov F. V. (2016). View on the pipe. Sibirskaia neft', (2), p. 36. [in Russian language]

+ - Purchase digital version of a single article Click to collapse

This article is available in electronic format (PDF).

DOI: 10.14489/td.2016.08.pp.030-033

Copy the article DOI and follow the link https://id-spektr.ru/product/pokupka-elektronnoy-stati-iz-zhurnala-kontrol-diagnostika

Please specify the article DOI in the order comments.