Q345R钢焊接缺陷声发射信号的时频分析
Time-Frequency Analysis of AE Signals Arisen from Q345R Steel Welding Defects
摘 要
利用短时傅里叶变换(STFT)、Wigner-Ville分布(WVD)、小波变换(WT)、Hilbert-Huang变换(HHT)四种时频分析方法对含焊接夹渣的Q345R钢在弯曲过程中各个阶段的声发射信号进行比较研究, 确定了各个阶段声发射信号的时频特性及能量分布。研究结果表明, 弯曲变形过程中, 各个阶段的声发射信号各不相同; HHT具有最高的时频分辨率, WT次之, WVD紧随其后, STFT最差; 弹性变形阶段信号的能量主要分布在25~80 kHz之间, 塑性变形阶段信号的能量主要集中在80~120 kHz之间, 裂纹扩展阶段信号的能量主要集中在140~170 kHz之间。
Q345R钢
声发射
时频分析法
Welding defect
Q345R steel
Acoustic emission
Time-frequency analysis
Abstract
This work addresses and compares the application of time-frequency analysis methodologies such as short-time fourier transform, wigner-ville distribution, wavelet transform and Hilbert-Huang transform for the analysis of acoustic emission signals as obtained from different deform stages in bending test of Q345R steel containing welding slag. The results are thoroughly discussed and show that the signal is characteristic of significant difference in each deform stage and Hilbert-Huang transform is better than other time-frequency analysis methodologies, in addition, the energy distribution of elastic stage is between 25~80 kHz and the plastic stage is between 80~120 kHz. While the frequency of crack propagation is distributed all over the frequency range and the energy is distributed between 140~170 kHz.
中图分类号 TG441.7, TB52.9 DOI 1000-6656(2014)09-0019-06
所属栏目 试验研究
基金项目 福建省质量技术监督局科技资助项目(FJQI201008)
收稿日期 2013/9/12
修改稿日期
网络出版日期
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备注熊亚飞(1987-), 男, 硕士, 主要从事无损检测方面研究。
引用该论文: XIONG Ya-fei,LI Qiang,YE Hui. Time-Frequency Analysis of AE Signals Arisen from Q345R Steel Welding Defects[J]. Nondestructive Testing, 2014, 36(9): 19～24
熊亚飞,李强,叶辉. Q345R钢焊接缺陷声发射信号的时频分析[J]. 无损检测, 2014, 36(9): 19～24
被引情况:
【1】吴旭景,杜斌,叶陈, "基于EMD和小波分解的管道泄漏声发射源定位",无损检测 37, 60-63(2015)
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参考文献
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【2】ENNACEUR C, LAKSIMI A, Herve C, et al. Monitoring crack growth in pressure vessel steels by the acoustic emission technique and the method of potential difference［J］. International Journal of Pressure Vessels and Piping,2006,83(3):197-204.
【3】JOSELIN R, CHELLADURAI T. Burst pressure prediction of composite pressure chambers using acoustic emission technique: a review［J］. Journal of Failure Analysis and Prevention,2011,11(4):344-356.
【4】XIAO H Q, WANG H W, YU H M, et al. Failure analysis on fracture of 16Mn steel［J］. Advanced Materials Research,2013,690:118-121.
【5】ROBERTS T M, TALEBZADEH M. Fatigue life prediction based on crack propagation and acoustic emission count rates［J］. Journal of Constructional Steel Research,2003,59(6):679-694.
【6】YU J, ZIEHL P, ZRATE B, et al. Prediction of fatigue crack growth in steel bridge components using acoustic emission［J］. Journal of Constructional Steel Research,2011,67(8):1254-1260.
【7】KHAN S A, CHIVAVIBUL P, SEDLAK P, et al. Analysis of acoustic emission signals during tensile deformation of Fe-Si steels with various silicon contents［J］. Metallurgical and Materials Transactions A,2013:1-12.
【8】SCHIAVI A, NICCOLINI G, TARIZZO P, et al. Acoustic emissions at high and low frequencies during compression tests in brittle materials［J］. Strain,2011,47(s2):105-110.
【9】LU C, DING P, CHEN Z. Time-frequency analysis of acoustic emission signals generated by tension damage in CFRP［J］. Procedia Engineering,2011,23:210-215.
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