Application of classification neural networks for identification of damage stages of degraded low alloy steel based on acoustic emission data analysis

• Autorzy: Krajewska-Śpiewak Joanna , Lasota Igor , Kozub Barbara

Identyfikatory

DOI

10.1007/s43452-020-00112-3

• Języki publikacji: EN

Abstrakty

EN

The paper presents the influence of low alloy steel degradation on the acoustic emission (AE) generated during static tension of notched specimen. The material was cut from a technological pipeline long-term operated in the oil refinery industry. Comparative analysis of AE activity generated by damage process of degraded and new material has been carried out. The different AE parameters were used to detect different stages of fracture process of low alloy steel under quasi-static tensile test. Neural networks with three layers were created with Broyden–Fletcher–Goldfarb–Shanno learning algorithm for a database analysis. The different AE parameters were included in the input layer. Classification neural networks were created in order to determine the stages of material degradation. The results obtained from the carried out studies will be used as the basis for new methodology development of the assessment of the structural condition of in-service equipment.

Słowa kluczowe

EN

low alloy steel; static stretching; technological pipeline

PL

stal niskostopowa; rozciąganie statyczne; rurociąg technologiczny

• Wydawca: Springer ; Wrocław University of Science and Technology
• Czasopismo: Archives of Civil and Mechanical Engineering
• Rocznik: 2020
• Tom: Vol. 20, no. 4
• Strony: 156--165
• Opis fizyczny: Bibliogr. 23 poz., rys., wykr.

Twórcy

autor

Krajewska-Śpiewak Joanna

• Faculty of Mechanical Engineering, Production Engineering Institute, Cracow University of Technology, Al. Jana Pawła II 37, 31‑864 Kraków, Poland

autor

Lasota Igor

• PKN Orlen S.A., Chemików 7, 09‑411 Płock, Poland

autor

Kozub Barbara

• Faculty of Materials Science and Physics, Institute of Material Engineering, Cracow University of Technology, Al. Jana Pawła II 37, 31‑864 Kraków, Poland

Bibliografia

• [1] Grosse CU, Ohtsu M. Acoustic emission testing, basics for research-applications in civil engineering. Berlin: Springer; 2008. p. 414.
• [2] Dunegan HL, Harris DO, Tatro CA. Fracture analysis by use of acoustic emission. Eng Fract Mech. 1968;1:105–22.
• [3] Ono K. Acoustic emission in materials research-a review. J AE. 2011;29:284–308.
• [4] Lazarev A, Vinogradov A. About plastic instabilities in iron and power spectrum of acoustic emission. J Acoust Emiss. 2009;27:144–56.
• [5] Almeida DM, Maia NS, Bracarense AQ, Medeiros EB, Maciel TM, Santos MA. Characterization of steel pipeline damage using acoustic emission technique. Soldagem Insp. 2007;12:55–62.
• [6] Lyasota I, Kozub B, Gawlik J. Identification of the tensile damage of degraded carbon steel and ferritic alloy-steel by acoustic emission with in situ microscopic investigations. Arch Civil Mech Eng. 2019;19:274–85.
• [7] Yang D, Yang L, Dong-ming F. Monitoring damage evolution of steel strand using acoustic emission technique and rate process theory. J Cent South Univ. 2014;21:3692–7.
• [8] Sahoo S, Jha BB, Sahoo TK. Acoustic emission study of deformation behaviour of sensitised 304 stainless steel. Energy Mater. 2014;9:1336–422.
• [9] Mukhopadhyay CK, Phaniraj C, Jayakumar T, Samuel KG. Study of tensile behaviour of thermally aged alloy D9 wrapper tubes of fast breeder reactor using acoustic emission. Strength Fract Complex. 2014;8:219–29.
• [10] Marsudi M. Study of acoustic emission during tensile test of mild steel plate, 8th international conference on heat transfer, fluid mechanics and thermodynamics. 2011; 11–13.
• [11] Zou S, Yan F, Yang G, Sun W. The identification of the deformation stage of a metal specimen based on acoustic emission data analysis. Sensors. 2017;17(4):789.
• [12] Akbari M, Ahmadi M. The application of acoustic emission technique to plastic deformation of low carbon steel. Phys Procedia. 2010;3:795–801.
• [13] Wang HW, Yu HM, Xiao HQ, Han ZY, Luo HY. Steel damage based on acoustic emission. Mater Res Innov. 2015;19:288–91.
• [14] Lee CS, Huh JH, Li DM, Shin DH. Acoustic emission behaviour during tensile tests of low carbon steel welds. ISIJ Int. 1999;39:365–70.
• [15] Penglin Z, Yuan S, Zhiqiang Z, Yaxing X. Application of acoustic emission technique in q345e steel tensile damage detection. J Gansu Sci. 2015;2:83–7.
• [16] Mukhopadhyay CK, Jayakumar T, Raj B, Ray KK. Acoustic emission during tensile deformation of pre-strained nuclear grade AISI type 304 stainless steel in the unnotched and notched conditions. J Mater Sci. 2007;42:5647–56.
• [17] Máthis K, Prchal D, Novotny R, Hähner P. Acoustic emission monitoring of slow strain rate tensile tests of 304L stainless steel in supercritical water environment. Corros Sci. 2011;53:59–63.
• [18] Lee JK, Lee JH, Lee SP, Son IS, Bae DS. Acoustic emission and ultrasonic wave characteristics in TIG-welded 316 stainless steel. Met Mater Int. 2014;20:483–8.
• [19] Penkin AG, Terent’ev VF, Roshchupkin VV, Slizov AK, Sirotinkin VP. Acoustic emission analysis of the stages of deformation of TRIP steel. Russ Metall. 2017;4:306–11.
• [20] ASTM A335 Standard Specification for Seamless Ferritic Alloy-Steel Pipe for High-Temperature Service.
• [21] EN 13554 : 2011 Non-destrucitve testing - Acoustic Emission testing - General principles.
• [22] Ohno K, Ohtsu M. Crack classification in concrete based on acoustic emission. Constr Build Mater. 2010;24:2339–466.
• [23] Fowler TJ, Blessing JA, Conlisk PJ, Swanson TL. The MONPAC System, world meeting on acoustic emission. Charloue. N. Carolina, March 1989.

Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)