Stable and unstable fatigue prediction for A572 structural steel using acoustic emission (original) (raw)
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Prediction of fatigue crack growth in steel bridge components using acoustic emission
Journal of Constructional Steel Research, 2011
The correlation of acoustic emission (AE) signal characteristics with crack growth behavior is of paramount importance to structural health monitoring and prognosis for in-service steel bridges. Relationships between AE absolute energy rate and crack growth rate are developed and presented. The relationships are based on experimental investigations intended to represent conditions found for in-service steel bridges. The approach presented is independent of the stress intensity range, which may simplify the life prediction procedure because stress intensity range is not always well defined in actual bridge components. Fatigue tests were performed to detect AE signals from fatigue cracks using compact tension (CT) specimens made of ASTM A572G50. Noise induced AE signals were filtered through a combined approach involving Swansong II Filters and investigation of waveforms, which are appropriate for data filtering and interpretation of field tests. Based on the experimental data and presented model, procedures for predicting crack extension and remaining fatigue life were carried out. Agreement between the predicted cracks and actual cracks verified the presented model and procedure. The study indicates that AE absolute energy rate may be more suitable than count rate in fatigue life prediction for the material of interest.► A crack growth prognosis methodology based on AE absolute energy rate is presented. ► Agreement between predicted cracks and actual cracks is demonstrated. ► Absolute energy rate rather than count rate is utilized in the model. ► The use of absolute energy rate improves the fatigue life prediction for steel bridges.
Fatigue and fracture assessment of cracks in steel elements using acoustic emission
2011
Single edge notches provide a very well defined load and fatigue crack size and shape environment for estimation of the stress intensity factor K, which is not found in welded elements. ASTM SE(T) specimens do not appear to provide ideal boundary conditions for proper recording of acoustic wave propagation and crack growth behavior observed in steel bridges, but do provide standard fatigue crack growth rate data. A modified versions of the SE(T) specimen has been examined to provide small scale specimens with improved acoustic emission(AE) characteristics while still maintaining accuracy of fatigue crack growth rate (da/dN) versus stress intensity factor (∆K). The specimens intend to represent a steel beam flange subjected to pure tension, with a surface crack growing transverse to a uniform stress field. Fatigue test is conducted at low R ratio. Analytical and numerical studies of stress intensity factor are developed for single edge notch test specimens consistent with the experimental program. ABAQUS finite element software is utilized for stress analysis of crack tips. Analytical experimental and numerical analysis were compared to assess the abilities of AE to capture a growing crack.
Quantitative Relationship between Strain and Acoustic Emission Response in Monitoring Fatigue Damage
Jurnal Teknologi, 2013
This study was carried out to investigate the relationship between the strain and acoustic emission (AE) signals, thus, to confirm the capability of AE technique to monitor the fatigue failure mechanism of a steel component. To achieve this goal, strain and AE signals were captured on the steel specimen during the cyclic fatigue test. Both signals were collected using specific data acquisition system by attaching the strain gauge and AE piezoelectric transducer simultaneously at the specimen during the test. The stress loading used for the test was set at 600 MPa, and the specimens were fabricated using the SAE 1045 carbon steel. The related parameters for both signals were determined at every 2000 seconds until the specimen failed. It was found that a meaningful correlation of all parameters, i.e. amplitude, kurtosis and energy, was established. Finally, all AE parameters are correlated with the damage values, which have been estimated using the Coffin-Manson model. Hence, it was suggested that the AE technique can be used as a monitoring tool for fatigue failure mechanism in a steel component.
Characterization of Fatigue Damage in 304L Steel by an Acoustic Emission Method
Procedia Engineering, 2013
The aim of this paper is to give a better understanding of damage mechanisms that control lifetime of austenitic stainless steel nuclear components under cyclic loading. The acoustic emission signals were analyzed, in order to identify the acoustic signatures corresponding to a specific damage mode. An unsupervised classification method allows differentiating signals resulting from the plastic deformation or fatigue crack growth. Both phenomena are the two main sources of acoustic emissions in isotropic materials. The main results are the classification of acoustic signals by multivariate statistical methods in different classes. A relation can be established between each class and the present deformation mechanisms and damage, and their order of appearance according to the loading amplitude.
Acoustic Emission Monitoring and Neural Network Fatigue Life Prediction in Steel Members
51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference<BR> 18th AIAA/ASME/AHS Adaptive Structures Conference<BR> 12th, 2010
Fatigue in all metal structural members, whether aviation or civil, possess similarities under comparable loading and environmental conditions, the main difference being that civil structures such as bridges are typically comprised of thicker members made of steel rather than aluminum. This paper applies the nondestructive evaluation (NDE) methodology used in aviation to monitor structural steel as in bridges for fatigue life prediction. It applies the nondestructive technique of acoustic emission (AE) to monitor the development of fatigue crack growth. A backpropagation neural network (BPNN) is utilized to perform fatigue life prediction from the early cyclic life data (25% of the experimental fatigue life). Testing of axially loaded notched specimens is completed and experimental results are used to generate the characteristic alternating stress versus fatigue life curves (S-N curves) for different notch lengths. These results were compared to those calculated from linear elastic fracture mechanics (LEFM) using the damage tolerance analysis software Air Force Grow (AFGROW). Fatigue prediction analysis focused on developing three distinct BPNN networks built to capture the entire range of the fatigue life spectrum. Two of the networks were specially designed for high cycle fatigue (HCF) prediction from AE amplitude histogram distributions. This network provided prediction results within 20% accuracy. This study demonstrates the legitimacy of applying AE monitoring and evaluation methodology in steel structures where failure is dominated by fatigue.
Adaptive Analysis of Acoustic Emissions for Fatigue Crack Growth Detection
2008
Acoustic Emission (AE) signals are collected during well controlled experiments, in order to detect a propagating crack inside a loaded structural component. From the numerous AE signals emitted from the loaded material one has to recognize those originated due to the crack growth. The detection, isolation and modeling of such signals require advanced techniques and experimental setups. Classic techniques such as feature extraction, as well as adaptive techniques, such as multi-model partitioning, are discussed, in an attempt to classify the AE waveforms and identify those related to the propagation of a crack. The aim is the successful estimation of the crack growth rate that may, subsequently, lead to improved reliability estimation and lifetime prediction of the component.
ACOUSTIC EMISSION MODEL OF FATIGUE CRACK IN LOW-CARBON STEEL
Transstellar Journal , 2019
One of the problems of the acoustic emission (AE) testing method is the parametric uncertainty of defect models. In this work, an empirical model of a fatigue crack is considered, which allows establishing quantitative relations between the parameters of a fatigue crack and AE data. The ambiguity in the interpretation of AE data is explained by the inhomogeneous stress-strain state of the material.
Ndt & E International, 1992
Acoustic emission (AE) is potentially an ideal technique for health monitoring of large structures due to the small number of sensors required and its high sensitivity. There has been much research conducted to characterize and provide qualitative understanding of the AE process in small specimens. Unfortunately, it is difficult to extend these results to real structures as the experimental data is dominated by geometric effects due to the small size of 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 was initiated in large 6082 T6 aluminium alloy plate specimens subjected to cyclic loading in the laboratory. A large specimen was used to eliminate signal reflections from the specimen edges and to enable signals from different wave modes to be separated in time. The signals were recorded using both resonant and non-resonant transducers attached to the surface of the specimens. Large numbers of AE signals were detected due to active fatigue crack propagation during the experiment. Analysis of experimental results from multiple crack growth events was used to characterize the modal and angular distributions of the radiated elastic waves. Experimental results are compared with finite element predictions to examine the mechanism of AE generation at the crack tip.
This paper proposes a comprehensive analytical and experimental methodology to monitor, in real time, fatigue crack growth and use physics based model for life prediction. The approach uses Acoustic Emission (AE) techniques to detect fatigue crack initiation and crack growth in aluminum materials used in aircraft structures. The quantification of damage rate induced by fatigue loading were investigated by analyzing the global effects of fatigue loading on the Acousto-Ultrasonic (AU) guided wave propagation in cracked samples. Mechanical properties degradation in terms of fatigue life was correlated with signal characteristics related to guided waves propagation. The aluminum alloy samples, with inserted precracks in the fastener holes, were tested mechanically in fatigue tension-tension cyclic loading with NDT monitoring techniques to quantify damage growth versus the fatigue cycle number. Nasgro analytical model, which integrates the crack growth rate, was used to produce a crack growth curve. Based on the correlations between crack propagation rates, acoustic emission rates and stress intensity factor range procedures are suggested for predicting critical fatigue life. The results indicate that by exploiting health monitoring data such; acoustic emission signals and guided waves features, coupled with analytical physic based models provides an effective methodology to estimate safety factor on life of the structure.