scholarly journals Fracture acoustic emission signals identification of stay cables in bridge engineering application using deep transfer learning and wavelet analysis

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Haohui Xin ◽  
Lu Cheng ◽  
Robin Diender ◽  
Milan Veljkovic
Keyword(s):  
Acoustic Emission ◽  
Wavelet Analysis ◽  
Transfer Learning ◽  
Engineering Application ◽  
Bridge Engineering ◽  
Stay Cables

scholarly journals Research on Failure Characteristics of Concrete Three-Point Bending Beams with Preexisting Cracks in Different Positions Based on Numerical Simulation

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Liuqun Zhao ◽  
Li Zheng ◽  
Hui Qin ◽  
Tiesuo Geng ◽  
Yonggang Tan ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Bearing Capacity ◽  
Failure Modes ◽  
Failure Process ◽  
Engineering Application ◽  
Tensile Failure ◽  
Engineering Structures ◽  
Failure Characteristics ◽  
Three Point Bending ◽  
Wide Range

Concrete three-point bending beams with preexisting cracks are widely used to study the growth process of I-II mixed mode cracks. Studying the failure characteristics of preexisting cracks at different locations on concrete three-point bending beams not only has important scientific significance but also has a wide range of engineering application backgrounds in the safety assessment of engineering structures. In this paper, through several numerical experiments, the influence of preexisting cracks at different positions on the failure characteristics of concrete three-point bending beams is studied, and three typical failure modes are obtained. The failure process of the specimens with three typical failure modes is discussed in detail, and it is pointed out that the crack failure mode is tensile failure. The change trends of bearing capacity, acoustic emission quantity, and acoustic emission energy of three typical failure modes are analyzed. The maximum bearing capacity, the maximum acoustic emission quantity, and energy of three failure modes of concrete three-point bending beams generally show an increasing trend.

Inspection of surface defects on stay cables using a robot and transfer learning

2020 ◽  
Vol 119 ◽  
pp. 103382
Author(s):  
Shitong Hou ◽  
Bin Dong ◽  
Haochen Wang ◽  
Gang Wu
Keyword(s):  
Transfer Learning ◽  
Surface Defects ◽  
Stay Cables

Detection of the Broken Wires in the Cables’ Hidden Parts (Anchorings) by Acoustic Emission

2006 ◽  
Vol 13-14 ◽  
pp. 345-350 ◽  
Author(s):  
Hasnae Zejli ◽  
A. Laksimi ◽  
C. Tessier ◽  
L. Gaillet ◽  
S. Benmedakhene
Keyword(s):  
Acoustic Emission ◽  
Elastic Energy ◽  
Necessary Conditions ◽  
Contact Strength ◽  
Surface Conditions ◽  
Stay Cables ◽  
Dynamic Bending ◽  
Steel Cables

Steel cables play an indispensable role in a number of rather diverse fields of applications. They are extensively used in suspension and stay cables bridges. It is important to be able to detect as precociously as possible the defects affecting their performance. They can present a healthy aspect over their observable lengths and be damaged in the hidden parts (anchorages). In this present study, Acoustic Emission (AE) is used in order to detect and to locate broken wires in the anchorage zones. The study of the behaviour of a broken wire in a cable under dynamic bending contribute to understand the origin of AE source and to discuss the necessary conditions of vibrating for detection. In this case, the phenomene source of AE is related to interwire friction caused by the redistribution of elastic energy on the recovery length of the broken wire and the repetition of the process joining-slip between wires. AE parameters are very influenced by the change of surface conditions, contact strength between wires and the recovery length of the broken wire. Several cables are evaluated in different surface conditions i.e. corroded, dry and oiled.

WAVELET ANALYSIS OF ACOUSTIC EMISSION SIGNALS BASED ON ALGEBRAIC WAVELETS

2016 ◽  
pp. 34-43
Author(s):  
K. O. Osipov ◽  
R. V. Zagidulin ◽  
T. R. Zagidulin
Keyword(s):  
Acoustic Emission ◽  
Wavelet Analysis

Study of Acoustic Emission of Wheel Passivation for Cermet Based on Super-Speed Grinding

2011 ◽  
Vol 328-330 ◽  
pp. 796-800
Author(s):  
Li Guo ◽  
Hou Bin Du ◽  
Xiao Min Sheng ◽  
Ke Li Peng ◽  
Tan Jin ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Wavelet Analysis ◽  
Monitoring Method ◽  
Wavelet Energy ◽  
Grinding Conditions ◽  
Nonlinear Relation ◽  
Relation Model ◽  
On Line ◽  
Viable Method ◽  
Table Speed

In this paper, there are two kinds of material (cermet and cemented carbide) to be used. Different grinding conditions were performed for evaluation of RMS of acoustic emission(AE) signals and understanding the effect of each grinding parameter on AE RMS during grinding process. A kind of on-line monitoring method based on wavelet analysis and acoustic emission was raised and the nonlinear relation model between AE RMS,wavelet energy coefficients and wheel passivation state was built. During the process,the wavelet analysis method was used to decompose the original signals for extracting wavelet energy coefficients. The results of experiments indicates that AE RMS increases with increasing table speed;The corresponding relation between AE RMS and table speed is good and could take the table speed as the main parameter for studying wheel passivation state. As a result, the nonlinear relation model can monitor the wheel passivation degree on-line accurately through training. This provides a kind of viable method which has very high practical value for confirming the wheel dressing cycle.

Research and Analysis on Rock Acoustic Emission Wave Characteristics

2014 ◽  
Vol 638-640 ◽  
pp. 534-537
Author(s):  
Jian Ping He
Keyword(s):  
Acoustic Emission ◽  
Wavelet Analysis ◽  
Laboratory Tests ◽  
Low Frequency ◽  
Development Trend ◽  
Signal Wave ◽  
Original Signal ◽  
Great Efficiency ◽  
Wave Characteristics ◽  
Ae Signal

Analyzing wave behavior on acoustic emission laboratory tests from relationship between stress and AE rate , the rock AE signal wave in laboratory is decomposed into high and low frequency elements. Analysis and compare with the details elements include, the approximation elements and original AE wave, the results show that rock AE wave characteristics are not same in the course of transform fracture on stages, found AE wave characteristics storehouse, it is a matter of great significance for utilizing monitoring and prediction regularity and development trend in the course of fracture transform. The error between the original signal and the signal of wave coefficient of the approximation elements reconstructed is minor to, wavelet analysis makes accuracy and reliability of rock AE wave characteristics monitoring and prediction improved, States that wavelet analysis is a great efficiency method.

Sign in / Sign up

Export Citation Format

Share Document