The Analysis Spectrum of Austenite Transformation on Acoustic Emission Signals

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Abstract:

There are the results of the acoustic emission (AE) signals spectrum modification during steel 30XGSA heating near the austenite transformation intervals. It is established in the AE signals spectrum during heating depend on steel phase structure. It makes possible the application of AE method for determination the austenite transformation borders. The critical points of austenite formations and austenite decay are based on heat treatment technologies. It is known, that there are phenomenon of steels properties modification without structure modification not for from phase transformation borders. This was very convenient for detecting the particles with foregone energy characteristics.

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1114-1117

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October 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] S. G. Taylor, H. Jeong, J. K. Jang, G. Park, K. M. Farinholt, M. D. Todd, and C. M. Ammerman, Full-scale fatigue tests of CX-100 wind turbine blades. Part II: analysis, in SPIE Smart Structures/NDE, San Diego, California, 2012, pp. 83430Q-10.

DOI: 10.1117/12.917497

Google Scholar

[2] S. R. Anton, et al., Multi-source energy harvesting for wind turbine structural health monitoring node, presented at the Advances in Structural Health Management andComposite Structures, Jeonju, Korea, (2012).

Google Scholar

[3] LIM J, MICRO K T. Cracking in stainless steel pipe detection by using acoustic emission and crest factor technique. Instrumentation and Measurement Technology Conference. Warsaw, Poland, May 1-3, 2007[C], IEEE Xplore: 1-3.

DOI: 10.1109/imtc.2007.379224

Google Scholar

[4] PAULO R, AGUIAR P J A, SEMI E C, et al. In-process grinding monitoring by acoustic emission. 2004[C], ICASSP04, (5): 405-408.

Google Scholar

[5] RAVINDRA H V. Some aspects of acoustic emission signal processing [J]. Journal of Materials Processing Technology. 2001, 109: 242~247.

DOI: 10.1016/s0924-0136(00)00805-0

Google Scholar

[6] KOICHI K, KOICHI N, SHIGERU T. FPGA-based lifting wavelet processor for real-time signal detection [J]. Signal Processing, 2004, 84: 1931-(1940).

DOI: 10.1016/j.sigpro.2004.06.020

Google Scholar

[7] LIM J, MICRO K T. Cracking in stainless steel pipe detection by using acoustic emission and crest factor technique. Instrumentation and Measurement Technology Conference. Warsaw, Poland, May 1-3, 2007[C], IEEE Xplore: 1-3.

DOI: 10.1109/imtc.2007.379224

Google Scholar

[8] JITSUKAWA N, OGAWA T, KANADA H et al. Time-frequency analysis of impact sound of composite materials. Proceedings of the 41st SICE Annual Conference SICE 2002[C]. 1076-1079.

DOI: 10.1109/sice.2002.1195327

Google Scholar

[9] Godwin, G. C., Graebe, S. F., & Salgado, M. E. (2001). Control System Design. Prentice Hall, Upper Saddle River, New Jersey 07458.

DOI: 10.1002/acs.675

Google Scholar

[10] Golub, G. H. & Loan, C. F. V. (1989). Matrix Computations. Johns Hopkins University Press. pp.557-558.

Google Scholar