Zerstörungsfreie Messmethoden zur Bestimmung des Warmauslagerungszustandes von Aluminiumlegierungen am Beispiel der Legierung EN AW-6082. Non-destructive testing methods for determining the age-hardening condition of aluminium alloys using the alloy EN AW

2010 ◽  
Vol 41 (8) ◽  
pp. 646-651 ◽  
Author(s):  
N. Grittner ◽  
D. Bormann ◽  
R. Springer ◽  
W. Reimche ◽  
Fr.-W. Bach
2014 ◽  
Vol 605 ◽  
pp. 139-142
Author(s):  
Seong Uk Hong ◽  
Yong Taeg Lee ◽  
Seung Hun Kim ◽  
J.H. Na

Recently, the interest in maintenance and repair of existing concrete structures have increased, and it is typical to use non-destructive testing methods such as rebound hardness test or ultrasonic pulse velocity method to execute maintenance and repair of structures efficiently. Many non-destructive testing methods are being used in practice such as at construction sites, but verification for site applications are quite inadequate. Thus, this study intends to evaluate the applicability of Impact Echo Method which is one of the non-destructive testing methods using stress wave. Total of four specimens were planned and produced. The thickness of concrete slab members was estimated using I.E(OLSENs Freedom Data PC with Win.TFS Software Version 2.5.2). The estimated materials of concrete members by IE was found to be IE-1 specimen 178mm, IE-2 specimen 197mm, IE-3 specimen 191mm, and IE-4 specimen 263mm, and the error rate was found to be 4.22%~18.67% (average 9.6%), showing that they are relatively well in agreement. In this study, the experiments were executed with the objective of estimating the thickness of concrete slab members using Impact Echo Method. Through this study, the applicability of thickness estimation in concrete slab members using impact echo method could be confirmed.


2013 ◽  
Vol 592-593 ◽  
pp. 553-556
Author(s):  
František Vlasic ◽  
Josef Volák ◽  
Libor Nohál ◽  
Pavel Mazal ◽  
Filip Hort

This paper deals with the basic research of cyclic damage during the initial stages of fatigue process using the non-destructive testing methods. The acoustic emission method was used for monitoring of the microstructure changes during fatigue loading. The electrical potential measurements of specimen and microscopic observation were used mainly to detect the first short cracks and their propagation. The fatigue tests at room temperature were conducted on titanium alloy and creep-resistant steel specimens under bending and tension loading. The aim of the study was to compare the acoustic emission signal at different types of loading until fracture and to analyze in detail the signal changes in initial stages of fatigue process. This analysis was primarily based on the waveform similarity and division into classes. The results show the high sensitivity of the acoustic emission technology in the transition from the stage of surface relief evolution to the stage of crack nucleation and propagation.


1993 ◽  
Vol 46 (4) ◽  
pp. 133-138 ◽  
Author(s):  
Patricio A. A. Laura

This article concerns the problem of evaluating the `structural health’ of cables or ropes by means of non-destructive testing methods. Special emphasis is placed upon electromagnetic techniques and the acoustic emission method.


2018 ◽  
Vol 207 ◽  
pp. 01001
Author(s):  
Tu Quynh Loan Ngo ◽  
Yu-Ren Wang

In the construction industry, to evaluate the compressive strength of concrete, destructive and non-destructive testing methods are used. Non-destructive testing methods are preferable due to the fact that those methods do not destroy concrete samples. However, they usually give larger percentage of error than using destructive tests. Among the non-destructive testing methods, the ultrasonic pulse velocity test is the popular one because it is economic and very simple in operation. Using the ultrasonic pulse velocity test gives 20% MAPE more than using destructive tests. This paper aims to improve the ultrasonic pulse velocity test results in estimating the compressive strength of concrete using the help of artificial intelligent. To establish a better prediction model for the ultrasonic pulse velocity test, data collected from 312 cylinder of concrete samples are used to develop and validate the model. The research results provide valuable information when using the ultrasonic pulse velocity tests to the inputs data in addition with support vector machine by learning algorithms, and the actual compressive strengths are set as the target output data to train the model. The results show that both MAPEs for the linear and nonlinear regression models are 11.17% and 17.66% respectively. The MAPE for the support vector machine models is 11.02%. These research results can provide valuable information when using the ultrasonic pulse velocity test to estimate the compressive strength of concrete.


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