The optical density histogram behavior of the photogrammetry of  the welding line in the radiography of steel with gamma ray

Sasanpour, M.T; Taheri, A

doi:10.24200/nst.2019.1033

The optical density histogram behavior of the photogrammetry of the welding line in the radiography of steel with gamma ray

Document Type : Research Paper

Authors

M.T Sasanpour

A Taheri

https://doi.org/10.24200/nst.2019.1033

Abstract

This paper tries to find a suitable probability distribution function for the optical density of the welding lines in the radiographic films. For this purpose, real gamma ray radiography films of the oil and gas pipelines were used in the operational areas of the National Oil Company. The number of the radiographic films was 4 and due to the unpredictability of the radiographic conditions and the existence of different regions on the surface of the films, histogram curves of the scattered data were selected to this investigation. More than 36 probability distribution functions were fitted on the histograms. 11 fitted probability functions with R-sq.≥0.95 were selected among the total functions. In addition, the final selected functions were fitted to 4 internal concavity (Suk Back) defects. Based on our obtained results, the best function was Pearson IV. Although a Gaussian function was also fitted and behaved quite well, but it was found that it is not perfect.

Highlights

BS EN 1993-1-8:2005 Eurocode 3, Design of steel structures. Design of joints.
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K.K. Lavania, Shivali,and R. Kumar, A comparative study of Image enhancement using histogram approach, IJCA. 32(5),0975 (2011).
S. Raja, S. Rajb and S. Kumarc, in: An Improved Histogram Equalization Technique for Image Contrast Enhancement, (Alpha College of Engineering, Bangalore, Karnataka, 9-11 July 2015, https://www.researchgate.net/publication/305421677), 6 pages.
L. Zhuang and Y. Guan1, Image enhancement via subimage histogram equalization based on mean and variance, COMPUT INTEL NEUROSC. Volume 2017, Article ID 6029892, 12 pages.
H. Kaur and N. Sohi, A study for applications of histogram in image enhancement, IJES, 6 (6), 59 (2017).
M.T. Sasanpour and A. Taheri, Determination of Probabilistic Distribution Function of Background and Defect Optical Densities for X-Ray Radiography Images of a Steel Plate, J NONDESTRUCT EVAL, 35, 61 (2016).

10. M.T. Sasanpour, E.I. Kosarina, Recommendations on selection of anode voltages in X-ray testing of steel specimens, Russ J Nondestruct Test, 47 (5), 48 (2011).

11. Laboratoire National Henri Becquerel (LNHB), www.nucleide.org.

12. ASTM Standard E94, U.S.A., Standard Guide for Radiographic Examination, (2010).

13. ASTM Standard E142-92, U.S.A., Standard Method for Controlling Quality of Radiographic Testing, (2000).

14. ASTM Standard E746, U.S.A., Standard Test Method for Determining Relative Image Quality Response of Industrial Radiographic Film Systems, (2007).

15. ASTM Standard E999, U.S.A., Standard Guide for Controlling the Quality of Industrial Radiographic Film Processing, (2010).

16. ASTM Standard E1032, U.S.A., Standard Test Method for Radiographic Examination of Weldments, (2006).

17. ASTM Standard E1079 U.S.A., Standard Practice for Calibration of Transmission Densitometers, (2017).

18. ASTM Standard E1390, U.S.A., Standard Guide for Illuminators Used for Viewing Industrial Radiographs, (2017).

19. ASTM Standard E1742, U.S.A., Standard Practice for Radiographic Examination, (2011).

20. ASTM Standard E1815, U.S.A., Standard Test Method for Classification of Film Systems for Industrial Radiography, (2008).

21. ASME BPVC Section V: Nondestructive Examination: Article 2 Radiographic Examination, U.S.A., (2015).

22. API International, Welding of Pipelines and Related Facilities: 11.1 Radiographic Test Methods, API Standard 1104, U.S.A., (2013).

23. BS EN ISO 5579: Non-destructive testing. Radiographic testing of metallic materials using film and X- or gamma rays. Basic rules, (2013)

24. BS EN ISO 19232-1: Non-destructive testing. Image quality of radiographs. Determination of the image quality value using wire-type image quality indicators, (2013)

25. BS EN ISO 17636-1:Non-destructive testing of welds. Radiographic testing. X- and gamma-ray techniques with film, (2013)

[26] BS EN 12681-1: Founding- Radiographic testing. Part 1: Film techniques, (2017).

Keywords

Histogram

Radiographic film

Probability distribution function

Pearson IV function

Gaussian function

20.1001.1.17351871.1398.40.3.14.0

BS EN 1993-1-8:2005 Eurocode 3, Design of steel structures. Design of joints.
E.D. Seletchi, and O.G. Duliu, Image processing and data analysis in computed tomography, ROM J PHYS.72, 764 (2007).
S. Inamdar et al. Multidimensional Probability Density Function Matching for Preprocessing of Multitemporal Remote Sensing Images, IEEE. 46 (4), 1243 (2008).
W. Kiadtikornthaweeyot, and A. R. L. Tatnall, in: Region of interest detection based on histogram segmentation for satellite image, (Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, Prague, Czech Republic, 249-255, 12–19 July 2016)
K.K. Lavania, Shivali,and R. Kumar, A comparative study of Image enhancement using histogram approach, IJCA. 32(5),0975 (2011).
S. Raja, S. Rajb and S. Kumarc, in: An Improved Histogram Equalization Technique for Image Contrast Enhancement, (Alpha College of Engineering, Bangalore, Karnataka, 9-11 July 2015, https://www.researchgate.net/publication/305421677), 6 pages.
L. Zhuang and Y. Guan1, Image enhancement via subimage histogram equalization based on mean and variance, COMPUT INTEL NEUROSC. Volume 2017, Article ID 6029892, 12 pages.
H. Kaur and N. Sohi, A study for applications of histogram in image enhancement, IJES, 6 (6), 59 (2017).
M.T. Sasanpour and A. Taheri, Determination of Probabilistic Distribution Function of Background and Defect Optical Densities for X-Ray Radiography Images of a Steel Plate, J NONDESTRUCT EVAL, 35, 61 (2016).