Damage identification based on wavelet packet analysis method

2016 ◽  
Vol 52 (1-2) ◽  
pp. 407-414 ◽  
Author(s):  
Yijin Chen ◽  
Shilin Xie ◽  
Xinong Zhang
Keyword(s):  
Damage Identification ◽  
Wavelet Packet ◽  
Analysis Method ◽  
Wavelet Packet Analysis

Structural Damage Identification Using Wavelet Packet Analysis and Neural Network

2006 ◽  
Vol 324-325 ◽  
pp. 205-208
Author(s):  
Qing Guo Fei ◽  
Ai Qun Li ◽  
Chang Qing Miao ◽  
Zhi Jun Li
Keyword(s):  
Neural Network ◽  
Structural Damage ◽  
Damage Identification ◽  
Wavelet Packet ◽  
Uniform Design ◽  
Network Models ◽  
Sampling Technique ◽  
Wavelet Packet Analysis ◽  
Neural Network Models ◽  
Network Training

This paper describes a study on damage identification using wavelet packet analysis and neural networks. The identification procedure could be divided into three steps. First, structure responses are decomposed into wavelet packet components. Then, the component energies are used to define damage feature and to train neural network models. Finally, in combination with the feature of the damaged structure response, the trained models are employed to determine the occurrence, the location and the qualification of the damage. The emphasis of this study is put on multi-damage case. Relevant issues are studied in detail especially the selection of training samples for multi-damage identification oriented neural network training. A frame model is utilized in the simulation cases to study the sampling techniques and the multi-damage identification. Uniform design is determined to be the most suitable sampling technique through simulation results. Identifications of multi-damage cases of the frame including different levels of damage at various locations are investigated. The results show that damages are successfully identified in all cases.

scholarly journals Tension Monitoring of Wedge Connection Using Piezoceramic Transducers and Wavelet Packet Analysis Method

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 364
Author(s):  
Xiaoyu Zhang ◽  
Liuyu Zhang ◽  
Laijun Liu ◽  
Linsheng Huo
Keyword(s):  
Energy Transfer ◽  
Stress Wave ◽  
Wavelet Packet ◽  
Active Sensing ◽  
Analysis Method ◽  
Wavelet Packet Analysis ◽  
Monitoring Method ◽  
Anchorage System ◽  
Steel Strand ◽  
Contact Surfaces

A steel strand is widely used in long span prestressed concrete bridges. The safety and stability of a steel strand are important issues during its operation period. A steel strand is usually subjected to various types of prestress loss which loosens the anchorage system, negatively impacting the stability of the structure and even leading to severe accidents. In this paper, the authors propose a wavelet packet analysis method to monitor the looseness of the wedge anchorage system by using stress wave-based active sensing. As a commonly used piezoceramic material, lead zirconate titanate (PZT) is employed with a strong piezoelectric effect. In the proposed active sensing approach, PZT patches are used as sensors and actuators to monitor the steel strand looseness. The anchorage system consists of the steel strand, wedges and barrel, which forms two different direct contact surfaces to monitor the tension force. PZT patches are pasted on the surface of each steel strand, corresponding wedge and barrel, respectively. Different combinations of PZTs are formed to monitor the anchoring state of the steel strand according to the position of the PZT patches. In this monitoring method of two contact surfaces, one PZT patch is used as an actuator to generate a stress wave and the other corresponding PZT patch is used as a sensor to detect the propagated waves through the wedge anchorage system. The function of these two PZTs were exchanged with the changing of transmission direction. The wavelet packet analysis method is utilized to analyze the transmitted signal between PZT patches through the steel strand anchorage system. Compared with the wavelet packet energy of received signals under different PZT combinations, it could be found that the wavelet packet energy increased with the increasing of anchorage system tightness. Therefore, the wavelet packet energy of received signal could be used to monitor the tightness of the steel strand during operation. Additionally, the wavelet packet energy of the received signals are different when the same PZT combination exchanges the energy transfer direction. With the comparison on the received signals of different combinations of PZTs, the optimal energy transfer path corresponding to different contact surfaces of the steel strand could be determined and the optimal experimental results are achieved.

Application of Wavelet Packet Analysis in Damage Alarming for Steel-Frame Structure

2012 ◽  
Vol 204-208 ◽  
pp. 2883-2886
Author(s):  
Ning Zhang ◽  
Zhuo Bin Wei ◽  
Zi Wang ◽  
Sen Wu
Keyword(s):  
Energy Spectrum ◽  
Response Function ◽  
Damage Identification ◽  
Wavelet Packet ◽  
Impulse Response Function ◽  
Steel Frame ◽  
Frame Structure ◽  
Wavelet Packet Analysis ◽  
Damage Alarming ◽  
Steel Frame Structure

The method of damage alarming based on wavelet packet analysis which applied on steel-frame structure is researched. Firstly, the method of damage identification based on wavelet packet analysis is introduced. Secondly, in view of the dependability of the method on the excitation, virtual impulse response function is brought in to enhance robustness of the method to the excitation. Lastly, through the steel-frame structure experimentation of damage alarming, the two damage modes of the structure are identified by the method based on wavelet packet energy spectrum. The experimentation results show that the effect of damage alarming to the steel-frame structure is completely obvious by wavelet packet analysis. Accordingly, this method has much application value for engineering.

scholarly journals Enhancement of shearography-based damage identification using best tree wavelet packet analysis

2018 ◽  
Vol 204 ◽  
pp. 06002
Author(s):  
Andrzej Katunin ◽  
Hernani Lopes ◽  
José Viriato Araújo dos Santos
Keyword(s):  
Wavelet Transforms ◽  
Structural Damage ◽  
Damage Identification ◽  
Experimental Testing ◽  
Wavelet Packet ◽  
High Sensitivity ◽  
Industrial Applications ◽  
Wavelet Packet Analysis ◽  
Destructive Testing ◽  
Signal Processing Methods

Shearography found many industrial applications as a non-destructive testing method due to its high spatial resolution and contactless measurements. However, to detect small structural damage, shearography should be enhanced by applying advanced signal processing methods to results of experimental testing. In this paper, the authors present an enhanced method based on the best tree wavelet packet analysis, which allows for extraction of the most informative nodes from the 2D wavelet packet decomposition tree. The proposed method is more effective than typical wavelet transforms due to its ability of adaptive selection of the best basis. The efficiency of the method was verified experimentally on damaged plates. The obtained results clearly show high sensitivity to the introduced small damage, which make the method attractive for industrial applications.

Fault Feature Extraction for Shaft System of Hydraulic Machinery Based on Wavelet Packet

2013 ◽  
Vol 437 ◽  
pp. 373-376
Author(s):  
Ye Zhou ◽  
Luo Ping Pan ◽  
Ping Ping Li
Keyword(s):  
Fault Diagnosis ◽  
Real Time ◽  
Online Monitoring ◽  
Wavelet Packet ◽  
Support Vector ◽  
Analysis Method ◽  
Wavelet Packet Analysis ◽  
Hydraulic Machinery ◽  
Shaft System ◽  
Fault Feature Extraction

Shaft fault is the most common fault for hydraulic machinery. In this paper, wavelet packet energy spectrum analysis method was used for multi frequency bands division of shaft monitoring signals. The variable bands frequency energy can construct feature vectors needed for fault diagnosis based on support vector machine, by integrating the procedure of wavelet packet analysis method and online monitoring technology, feature can be extracted in real time, and it make possible for real-time fault diagnosis and prediction of hydraulic machine.

Real-time localization of micro-damage in concrete beams using DIC technology and wavelet packet analysis

2021 ◽  
pp. 104198
Author(s):  
Kaiyang Zhou ◽  
Dong Lei ◽  
Jintao He ◽  
Pei Zhang ◽  
Pengxiang Bai ◽  
...  
Keyword(s):  
Real Time ◽  
Concrete Beams ◽  
Wavelet Packet ◽  
Wavelet Packet Analysis ◽  
Damage In Concrete
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