基于聲發射監測的316LN不銹鋼的疲勞損傷評價

張進; 柴孟瑜; 項靖海; 段權

doi:10.13374/j.issn2095-9389.2018.04.009

基于聲發射監測的316LN不銹鋼的疲勞損傷評價

doi: 10.13374/j.issn2095-9389.2018.04.009

西安交通大學化學工程與技術學院, 西安 710049

詳細信息

中圖分類號: TG142.33⁺1
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出版歷程
- 收稿日期: 2017-06-21

Fatigue damage evaluation of 316LN stainless steel using acoustic emission monitoring

School of Chemical Engineering and Technology, Xi'an Jiaotong University, Xi'an 710049, China

摘要

摘要: 疲勞裂紋的萌生與擴展容易導致壓力容器及管道的嚴重疲勞失效.因此就設備的安全可靠性而言,非常有必要對疲勞裂紋擴展過程進行監測,并對疲勞損傷程度進行評估.本文針對316LN不銹鋼材料進行疲勞實驗研究,利用直流電位法測量實驗中的裂紋長度,得到了材料的疲勞裂紋擴展曲線.利用聲發射技術對疲勞裂紋擴展過程進行監測,通過聲發射多參數分析對疲勞損傷狀態進行評價,同時建立了聲發射參數與線彈性斷裂力學參數之間的關系,并進行壽命預測.研究表明:聲發射能夠對316LN不銹鋼的疲勞裂紋損傷進行有效評估,聲發射累積參數如累積計數、累積能量和累積幅值曲線上的轉折點標志著疲勞裂紋進入快速擴展階段,這可以為工程人員提供失效預警;聲發射波形和頻譜分析表明,噪聲信號的幅值較小且信號持續時間較長,信號包含的頻率成分比較復雜,而裂紋擴展信號是突發型信號,衰減較快,信號頻率主要集中在80~170 kHz范圍內;聲發射計數率、能量率和幅值率與應力強度因子幅度以及疲勞裂紋擴展速率之間呈線性關系,裂紋長度預測結果與實測值接近.本研究工作對于工程結構的疲勞失效預警和剩余壽命預測具有重要意義.
- 316LN不銹鋼 /
- 疲勞裂紋擴展 /
- 聲發射 /
- 多參數分析 /
- 壽命預測
Abstract: The initiation and growth of fatigue cracks usually lead to serious fatigue failure of steel structures such as pressure vessels and pipelines. Therefore, for the safety and reliability of engineering structures, monitoring the fatigue crack growth and evaluating the severity of fatigue damage are important. An investigation of fatigue damage evaluation of 316LN stainless steel was presented by using the in situ acoustic emission (AE) monitoring technique. Fatigue crack propagation tests of 316LN stainless steel were carried out. The direct-current potential-drop method was used to measure fatigue crack propagation. At the same time, the AE technique was used to monitor propagation of the fatigue cracks in real time. The fatigue damage of 316LN stainless steel was qualitatively assessed by AE multi-parametric analyses such as the AE count, energy, and amplitude. Moreover, the quantitative relationships among AE parameters and the linear elastic fracture mechanics parameters were established for predicting the remaining fatigue life. The results show that the AE technique is effective for evaluating the severity of fatigue damage of 316LN stainless steel. The transition point on the curves of cumulated count, energy, and amplitude indicates that the fatigue crack propagates into the rapid crack propagation stage. This obvious change in AE could potentially provide failure warnings for researchers or engineers. Furthermore, the analyses of waveform and frequency show that the noise signal with low amplitude and long duration contains complex frequency components, whereas the crack propagation signal is a type of burst signal and the frequency is mainly distributed in the range from 80 to 170 kHz. In addition, the quantitative relations between fatigue crack propagation rate and AE rates such as the count rate, energy rate, and the amplitude rate were found to be linear, and these relations were used to predict fatigue crack length. The predicted fatigue crack lengths showed good agreement with the measured crack lengths. The results of the present investigation will be helpful for providing fatigue failure warnings and predicting the remaining fatigue life of engineering structures.
- 316LN stainless steel /
- fatigue crack propagation /
- acoustic emission /
- multi-parametric analysis /
- fatigue life prediction

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參考文獻(18)

[3]	Ennaceur C, Laksimi A, Hervé C, et al. Monitoring crack growth in pressure vessel steels by the acoustic emission technique and the method of potential difference. Int J Press Vessels Pip, 2006, 83(3):197
[5]	Han Z Y, Luo H Y, Zhang Y B, et al. Effects of micro-structure on fatigue crack propagation and acoustic emission behaviors in a micro-alloyed steel. Mater Sci Eng A, 2013, 559:534
[6]	Li L F, Zhang Z, Shen G T. Influence of grain size on fatigue crack propagation and acoustic emission features in commercial-purity zirconium. Mater Sci Eng A, 2015, 636:35
[7]	Moorthy V, Jayakumar T, Raj B. Influence of microstructure on acoustic emission behavior during stage 2 fatigue crack growth in solution annealed, thermally aged and weld specimens of AISI type 316 stainless steel. Mater Sci Eng A, 1996, 212(2):273
[8]	Chai M Y, Zhang J, Zhang Z X, et al. Acoustic emission studies for characterization of fatigue crack growth in 316LN stainless steel and welds. Appl Acoust, 2017, 126:101
[9]	Chai M Y, Zhang Z X, Song Y, et al. Assessment of fatigue crack growth in 316LN stainless steel based on acoustic emission entropy. Int J Fatigue, 2018, 109:145
[10]	Strantza M, Hemelrijck D V, Guillaume P, et al. Acoustic emission monitoring of crack propagation in additively manufactured and conventional titanium components. Mech Res Commun, 2017, 84:8
[11]	Morton T M, Smith S, Harrington R M. Effect of loading variables on the acoustic emissions of fatigue-crack growth. Exp Mech, 1974, 14(5):208
[12]	Roberts T M, Talebzadeh M. Acoustic emission monitoring of fatigue crack propagation. J Constr Steel Res, 2003, 59(6):695
[13]	Roberts T M, Talebzadeh M. Fatigue life prediction based on crack propagation and acoustic emission count rates. J Constr Steel Res, 2003, 59(6):679
[14]	Rabiei M, Modarres M. Quantitative methods for structural health management using in situ acoustic emission monitoring. Int J Fatigue, 2013, 49:81
[15]	Gagar D, Foote P, Irving P E. Effects of loading and sample geometry on acoustic emission generation during fatigue crack growth:Implications for structural health monitoring. Int J Fatigue, 2015, 81:117
[16]	Keshtgar A, Modarres M. Probabilistic approach for nondestructive detection of fatigue crack initiation and sizing. Int J Prognost Health Manage, 2016, 7:19
[17]	Chai M Y, Duan Q, Hou X L, et al. Fracture toughness evaluation of 316LN stainless steel and weld using acoustic emission technique. ISIJ Int, 2016, 56(5):875
[18]	Zhang Y B, Luo H Y, Li J R, et al. An integrated processing method for fatigue damage identification in a steel structure based on acoustic emission signals. J Mater Eng Perform, 2017, 26(4):1784
[20]	Kahirdeh A, Sauerbrunn C, Yun H, et al. A parametric approach to acoustic entropy estimation for assessment of fatigue damage. Int J Fatigue, 2017, 100:229
[22]	Paris P, Erdogan F. A critical analysis of crack propagation laws. J Basic Eng, 1963, 85(4):528
[23]	Yu J G, Ziehl P, Zárate B, et al. Prediction of fatigue crack growth in steel bridge components using acoustic emission. J Constr Steel Res, 2011, 67(8):1254