Wavelet packet transform for detection of single events in acoustic emission signals

被引:84
作者
Bianchi, Davide [1 ]
Mayrhofer, Erwin [1 ,2 ]
Groeschl, Martin [2 ]
Betz, Gerhard [2 ]
Vernes, Andras [1 ,2 ]
机构
[1] AC2T Res GmbH, A-2700 Wiener Neustadt, Austria
[2] Vienna Univ Technol, Inst Appl Phys, A-1040 Vienna, Austria
关键词
Event detection; Wavelet packet transform; Acoustic emission; Rolling contact fatigue; Rail-wheel contact; ROLLING-CONTACT FATIGUE; RAIL; WEAR; TRACK;
D O I
10.1016/j.ymssp.2015.04.014
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Acoustic emission signals in tribology can be used for monitoring the state of bodies in contact and relative motion. The recorded signal includes information which can be associated with different events, such as the formation and propagation of cracks, appearance of scratches and so on. One of the major challenges in analyzing these acoustic emission signals is to identify parts of the signal which belong to such an event and discern it from noise. In this contribution, a wavelet packet decomposition within the framework of multiresolution analysis theory is considered to analyze acoustic emission signals to investigate the failure of tribological systems. By applying the wavelet packet transform a method for the extraction of single events in rail contact fatigue test is proposed. The extraction of such events at several stages of the test permits a classification and the analysis of the evolution of cracks in the rail. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:441 / 451
页数:11
相关论文
共 50 条
[31]   Dynamic rock tensile failure under hydrostatic pressure analyzed with wavelet transform of acoustic emission signals [J].
Xu, Ying ;
Fu, Yan ;
Wang, Chonglang ;
Yao, Wei ;
Xia, Kaiwen .
ENGINEERING FRACTURE MECHANICS, 2024, 306
[32]   Application of the wavelet packet transform to vibration signals for surface roughness monitoring in CNC turning operations [J].
Garcia Plaza, E. ;
Nunez Lopez, P. J. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2018, 98 :902-919
[33]   Hyperspectral trace gas detection using the wavelet packet transform [J].
Salvador, Mark Z. ;
Resmini, Ronald G. ;
Gomez, Richard B. .
ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIV, 2008, 6966
[34]   ADVANCED DAMAGE DETECTION IN REINFORCED CONCRETE APPLYING ACOUSTIC EMISSION, WAVELET TRANSFORM AND SHANNON ENTROPY [J].
Das, Soumyadip ;
Datta, Aloke Kumar ;
Topdar, Pijush ;
Sengupta, Sanjay .
SURANAREE JOURNAL OF SCIENCE AND TECHNOLOGY, 2024, 31 (05) :1-11
[35]   Automated detection of atrial fibrillation in ECG signals based on wavelet packet transform and correlation function of random process [J].
Wang, Jibin ;
Wang, Ping ;
Wang, Suping .
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2020, 55
[36]   Characteristics Extraction of Acoustic Emission Signal Based on Wavelet Packet Decomposition [J].
Xiao, Denghong ;
Xiao, Xiaohong ;
Xiao, Ong ;
Quan, Dongliang ;
He, Tian ;
Liu, Xiandong .
2015 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM), 2015,
[37]   Application of the wavelet transform to acoustic emission signals for built-up edge monitoring in stainless steel machining [J].
Ahmed, Yassmin Seid ;
Arif, A. F. M. ;
Veldhuis, Stephen Clarence .
MEASUREMENT, 2020, 154
[38]   Analysis of acoustic emission signals using wavelet transformation technique [J].
Rao, S. V. Subba ;
Subramanyam, B. .
DEFENCE SCIENCE JOURNAL, 2008, 58 (04) :559-564
[39]   Detection of weak transient signals based on wavelet packet transform and manifold learning for rolling element bearing fault diagnosis [J].
Wang, Yi ;
Xu, Guanghua ;
Liang, Lin ;
Jiang, Kuosheng .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2015, 54-55 :259-276
[40]   Epileptic seizure detection based on imbalanced classification and wavelet packet transform [J].
Yuan, Qi ;
Zhou, Weidong ;
Zhang, Liren ;
Zhang, Fan ;
Xu, Fangzhou ;
Leng, Yan ;
Wei, Dongmei ;
Chen, Meina .
SEIZURE-EUROPEAN JOURNAL OF EPILEPSY, 2017, 50 :99-108