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Application of Arrival Time Profiles to AE Source Location by Neural Networks
Chlada, Milan ; Blaháček, Michal ; Převorovský, Zdeněk
The localization procedures using artificial neural networks (ANN) represent today highly effective, alternative approach to classical triangulation algorithms. Nevertheless, their application possibilities are limited due to several reasons. The main problems are in the collecting of sufficiently extensive training and testing data sets together with the non-portability of particular trained network to any other object. In recent time, a new ANN-based AE source location method using so-called signal arrival time profiles was proposed to overcome both limitations. The new way of signal arrival time characterization provides the ANN training on numerical models and allows the application of learned ANN on real structures of various scales and materials. In the paper, this new method is illustrated on experimental data obtained at complex aircraft structure part testing, and its remarkable advantages concerning the considerable extension of ANN application possibilities are discussed.
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Combined ESAM and DORT method in nonlinear ultrasonic spectroscopy
Vejvodová, Šárka ; Převorovský, Zdeněk ; Dos Santos, S.
Combination of ESAM (Excitation Symmetry Analysis Method) and DORT (Décomposition de l’Opérateur du Retournement Temporel) provides a powerful tool for detection and localization of defects by analysis of their nonlinear signature. Piezoelectric transducers are used for both excitation and data acquisition. Transmitters consequently emit the excitation signals and corresponding responses are measured by the array of receivers. The amplitude of excitation signals is variable as to separate the nonlinear parts of the measured signal. ESAM signal pre-processing is used for nonlinear parts extraction. Separated signal records form linear and nonlinear multistatic data matrices. DORT method is applied on data matrices to separate echoes of defects in the tested medium. Obtained data are used for evaluation of nonlinear parameters corresponding to separated defects and also for their localization. The procedure is completed by visualization of nonlinear signatures of detected defects.
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Lokalizace zdrojů akustické emise pomocí neuronových sítí na základě časových profilů
Chlada, Milan ; Blaháček, Michal ; Převorovský, Zdeněk
Correct localization of acoustic emission (AE) sources is a basic requirement in AE analysis and consequent evaluation of damage mechanism. The localization procedures using artificial neural networks (ANN) represent today highly effective, alternative approach to classical triangulation algorithms. Nevertheless, their application possibilities are limited due to problematic collecting of sufficiently extensive training and testing data sets together with the non-portability of particular trained network to any other object. A new ANN-based approach, using so-called signal arrival time profiles, is proposed to overcome both limitations. Such approach provides the ANN training on numerical models and allows the application of learned ANN on real structures of various scales and materials. This enables considerable extension of ANN application possibilities. New method is illustrated on experimental data obtained during pen-tests on a steel plate, and its remarkable advantages are discussed.
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OPTIMIZED NUMBER OF SIGNAL FEATURES FOR IDENTIFICATION OF AE SOURCES
Chlada, Milan ; Převorovský, Zdeněk
Artificial neural networks (ANN) are effective instruments for identification of AE sources. The proper selection of extracted data features is complicated task in general data recognition. Standard AE signal parameters are often redundant or not relevant in recognition problem. Modifications of standard AE signal features are proposed in this paper as to reduce data redundancy. Set of extracted AE parameters is optimized by factor analysis and sensitivity analysis of recognizing neural networks. This optimization is illustrated by recognition of AE sources arising during fatigue tests performed on aircraft structure parts. Optimized AE signal features cover enough information with minimized number of parameters.
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Acoustic emission of cyclical loaded aircraft structures
Blaháček, Michal ; Skála, J.
Aircraft structures fatigue failure is considerable risk of today´s aviation safety. The problem is usually solved by critical parts preventive replacement, regardless of parts real state. It is very expensive and uneconomical solution. NDT method capable to find the changes in the part, that are indication of crack creation and growth, would be very useful and money saving.Acoustic emission (AE) is a NDT procedure that is candidate for the method. In the Aeronautical Research and Test Institute (VZLÚ) set of cyclical fatigue tests was done. During the test, loaded sample AE activity was monitored, during the loading sequence pauses, the sample state was checked using NDT methods such us ultrasound, eddy current, optical methods, non-linear ultrasound, etc. Presented paper attends to desription and analysis of AE measurement on cyclical loaded aircraft structure.
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Expertní detekce příchodu signálu AE
Chlada, Milan
Accurate acoustic emission (AE) source location is the primary goal of the defect anylysis following the AE signal detection. The source localization is mostly based on arrival time differences of signals recorded by several transducers. Considerable signal distortion happens during the wave propagation through the solid. Inaccurate determination of signal onset and arrival time differences respectively, are the greatest sources of localization errors.Especially, in a case of figher requirements on accuracy and robustness, the results of currently used localization methods appear to be insufficient. In the paper, recently improved version of the new signal-shape based algorithm, modelling an expert system of the elastic wave arrival detection, is introduced. In many applications, this method, based on signal energy and local gravity center evolution, has been proved as rugged enough, fast and easily applicable.
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Vliv nejistoty v určení časových diferencí na přesnost lokalizace zdroje akustické emise
Blaháček, Michal
Acoustic emission (AE) is a non-destructive testing method using acoustic, mostly ultrasonic, waves emitted by AE sources and propagating in structure to find out desired information about the tested construction or sample state. The AE source location is its basic (and very important) parameter. Most of location algorithms use time differences of AE signal arrival times from the source to different transducers and acoustic wave propagation velocity as input data.However, the parameters are often difficult to obtain in real conditions, especially out of laboratory and in the working conditions where acoustic noise is presented. Main goal of this paper is to analyze influence of time differences uncertainty (i.e. errors in the detected times)and the elastic wave velocity uncertainty on AE source 2-D location accuracy. The analysis will be done for a classic triangulation location algorithm.
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