基于声发射及小波奇异性的钢轨损伤检测

PDF(913 KB)

振动与冲击 ›› 2017, Vol. 36 ›› Issue (2) : 196-200.

论文

基于声发射及小波奇异性的钢轨损伤检测

宋阳1 ，吴凡1 ，刘德扣1 ，刘晓舟2 ，倪一清2

作者信息 +

Rail damage detection method based on acoustic emission and wavelet singularity

SONG Yang1,WU Fan1,LIU Dekou1,LIU Xiaozhou2,NI Yiqing2

Author information +

文章历史 +

摘要

很多重大脱轨事件都与钢轨的损伤密切相关，因此，对在役钢轨进行定期损伤检测显得尤为重要。本研究首先运用声发射原理，通过对在役钢轨损伤前后监测系统所采集的数据信号进行时域及频域的分析，根据有损信号的能量谱特点，判断钢轨中损伤的存在。其次，运用小波奇异性检测原理探讨研究了定位损伤。通过分析各种连续小波变换算法的结果，得出à Trous算法在奇异性检测中能够较准确判断出奇异点位置。因此，结合声发射原理和小波处理的方法的无损监测可应用于在役钢轨的损伤检测和定位，对铁路钢轨损伤进行检测和预报。

Abstract

Many major derail accidents are closely related to the rail damage,so the study on the rail flaw detection technology is particularly important nowadays. The study is aiming at analyzing and comparing the characteristics of signals data before and after destruction,collected by a damage detection system. The damage and defect were judged by the differences between the processed data of destructive signals and nondestructive ones in time and frequency domain and according to the energy spectrum features. Whats more,the locations of defects and damages were obtained by virtue of the singularities of destructive signals using three wavelet singularity analysis methods,including continuous wavelet transform,Mallat algorithm and à Trous algorithm. It is found that à Trous algorithm can give quite accurate information about real damage locations,which shows that this method can be used in the real damage detection for rails and provide us more precise defect location information.

导出引用

宋阳1,吴凡1,刘德扣1,刘晓舟2,倪一清2. 基于声发射及小波奇异性的钢轨损伤检测[J]. 振动与冲击, 2017, 36(2): 196-200

SONG Yang1,WU Fan1,LIU Dekou1,LIU Xiaozhou2,NI Yiqing2. Rail damage detection method based on acoustic emission and wavelet singularity[J]. Journal of Vibration and Shock, 2017, 36(2): 196-200

参考文献

[1] Li Y, Wilson J, Tian G Y. Experiment and simulation study of 3D magnetic field sensing for magnetic flux leakage defect characterisation[J]. NDT & E International, 2007, 40(2):179-184.
[2] Chacón Muñoz J M, García Márquez J P, Papaelias M. Railroad inspection based on ACFM employing a non-uniform B-spline approach[J]. Mechanical Systems and Signal Processing, 2013, 40(2) :605-617.
[3] Song Z, Yamada T, Shitara H, et al. Detection of Damage and Crack in Railhead by Using Eddy Current Testing[J]. Journal of Electromagnetic Analysis and Applications, 2011, 3(12) :546-550.
[4] Edwards R S, Dixon S, Jian X. Characterisation of defects in the railhead using ultrasonic surface waves[J]. NDT & E International, 2006,39(6): 468-475.
[5] Coccia S, Phillips R, Nucera C, et al. UCSD/FRA non-contact ultrasonic guided-wave system for rail inspection[C]// An update (2011) Proceedings of SPIE - The International Society for Optical Engineering, 7981.
[6] Kenderian S, Djordjevic B B, Cerniglia D, et al. Dynamic railroad inspection using the laser-air hybrid ultrasonic technique[J]. Non-Destructive Testing and Condition Monitoring,2006, 48(6): 336-341.
[7] Bruzelius K, Mba D, An initial investigation on the potential applicability of Acoustic Emission to rail track fault detection[J]. NDT & E International, 2004, 37(7): 507-516.
[8] Bollas K, Papasalouros D, Kourousis D, et al. Acoustic emission monitoring of wheel sets on moving trains[J]. Construction and Building Materials, 2013,48:1266-1272.
[9] Hesse D, Cawley P. Surface wave modes in rails[J]. Acoustical Society of America, 2006,5(15):733-740.
[10] Chong M L, Joseph L R, Younho C. A guided wave approach to defect detection under shelling in rail[J], NDT&E International,2009,42:174-180.
[11] Coccia S, Bartoli I, Marzani A, et al. Numerical and experimental study of guided waves for detection of defects in the rail head[J], NDT&E International,2011, 44:93-100.
[12] 何浩祥,孙立,闫维明,等.基于小波分析的结构损伤信号奇异性检测[J].工业建筑,2007,S1:204-207.
HE Hao-xiang, SUN Li, YAN Wei-ming, et al. Singularity detection for structural damaged signals based on wavelet analysis[J]. Industrial Construction,2007,S1:204-207.
[13] 张悦,杜守军,张丽梅. 小波奇异性在钢结构损伤检测中的应用[J]. 河北科技大学学报,2010,31(2):151-157.
ZHANG Yue, DU Shou-jun, ZHANG Li-mei. Application of wavelet singularity to steel structural damage detection[J]. Journal of Heibei University of Science and technology,2010,31(2):151-157.
[14]邱颖,任青文,朱建华. 基于小波奇异性的梁结构损伤诊断[J]. 工程力学,2005,S1:146-151.
QIU Ying, REN Qing-wen, ZHU Jian-hua. A beam damage diagnosis based on wavelet singularity[J]. Engineering Mechanics,2005,S1:146-151.
[15] Yamagishi S, Ichiki M, Fujimoto S,et al. Characterization of the piezoelectric power generation of PZT ceramics under mechanical force[C]. 2013 Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS, DTIP 2013.
[16] Sakamoto W K, Marin-Franch P, Tunnicliffe D,et al. Lead zirconate titanate/polyurethane (PZT/PU) composite for acoustic emission sensors[M]//Conference on Electrical Insulation and Dielectric Phenomena (CEIDP), Annual Report:20-23.
[17] Song G, Gu H, Mo Y L, et al. Concrete structural health monitoring using embedded piezoceramic transducers[J]. Smart Materials and Structures, 2007, 16(4): 959.
[18] Qiu L, Yuan S F, Shi X L,et al. Design of piezoelectric transducer layer with electromagnetic shielding and high connection reliability[J]. Smart Materials and Structures,2012, 21(7): 075032.