Special features of acoustic emission from fatigue cracks in welded joints in oil pipes

1992 ◽  
Vol 25 (6) ◽  
pp. 295
Author(s):  
A.G. Golovinskii ◽  
A.V. Kiselev ◽  
A.M. Kotkis ◽  
N.F. Khokhlov ◽  
A.M. Shiryaev
Vestnik MEI ◽  
2017 ◽  
pp. 96-101
Author(s):  
Viktor V. Nosov ◽  
◽  
Alsu R. Yamilova ◽  
Nikolay A. Zelenskiy ◽  
Ilya V. Matviyan ◽  
...  

2006 ◽  
Vol 13-14 ◽  
pp. 23-28 ◽  
Author(s):  
C.K. Lee ◽  
Jonathan J. Scholey ◽  
Paul D. Wilcox ◽  
M.R. Wisnom ◽  
Michael I. Friswell ◽  
...  

Acoustic emission (AE) testing is an increasingly popular technique used for nondestructive evaluation (NDE). It has been used to detect and locate defects such as fatigue cracks in real structures. The monitoring of fatigue cracks in plate-like structures is critical for aerospace industries. Much research has been conducted to characterize and provide quantitative understanding of the source of emission on small specimens. It is difficult to extend these results to real structures as most of the experiments are restricted by the geometric effects from the specimens. The aim of this work is to provide a characterization of elastic waves emanating from fatigue cracks in plate-like structures. Fatigue crack growth is initiated in large 6082 T6 aluminium alloy plate specimens subjected to fatigue loading in the laboratory. A large specimen is utilized to eliminate multiple reflections from edges. The signals were recorded using both resonant and nonresonant transducers attached to the surface of the alloy specimens. The distances between the damage feature and sensors are located far enough apart in order to obtain good separation of guided-wave modes. Large numbers of AE signals are detected with active fatigue crack propagation during the experiment. Analysis of experimental results from multiple crack growth events are used to characterize the elastic waves. Experimental results are compared with finite element predictions to examine the mechanism of AE generation at the crack tip.


Author(s):  
A. Rastegaev ◽  
M. L. Linderov ◽  
D. L. Merson ◽  
M. A. Afanasyev ◽  
A. V. Danyuk

Author(s):  
Denghong Xiao ◽  
Tian He ◽  
Xiandong Liu ◽  
Yingchun Shan

A novel approach of locating damage in welded joints is proposed based on acoustic emission (AE) beamforming, which is particularly applicable to complex plate-like structures. First, five AE sensors used to obtain AE signals generated from damage are distributed on the surface of the structure in a uniform line array. Then the beamforming method is adopted to detect the weld joints in the area of interest rather than all the points of the whole structure, and to determine the location and obtain information of AE sources. In order to study the ability of the proposed method more comprehensively, a rectangular steel tube with welded joints is taken for the pencil-lead-broken test. The localization results indicate that the proposed localization approach can effectively localize the failure welded joints. This improvement greatly reduces the cost of computation and also improves the efficiency of localization work compared with the traditional beamforming.


Author(s):  
K M Holford ◽  
R Pullin ◽  
S L Evans ◽  
M J Eaton ◽  
J Hensman ◽  
...  

Structural health monitoring (SHM) is of paramount importance in the aircraft industry: not only to ensure the safety and reliability of aircraft in flight and to ensure timely maintenance of critical components, but also increasingly to monitor structures under test for airworthiness certification of new designs. This article highlights some of the recent advances in the acoustic emission (AE) technique as applied to SHM, and the new approaches that are crucial for the successful use of AE data for diagnostic purposes. These include modal analysis, enhanced location techniques, and novel signal processing approaches. A case study is presented on a landing gear component undergoing fatigue loading in which a linear location analysis using conventional techniques identified the position of fracture and final rupture of the specimen. A principal component analysis approach was used to separate noise signals from signals arising from fatigue cracks, which identified and located further fatigue crack positions, subsequently confirmed by magnetic particle inspection. Kernel probability density functions are used to aid visualization of the damage location.


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