Abstract
One of the biggest challenge for acoustic emission (AE) signal classification on real constructions is transfer from laboratory measurement on specimens to full scale. Detected AE responses are (among other factors) strongly influenced by propagation of waves in material and transfer function of sensor used. Propagation of elastic stress waves in plate of AISI 304 stainless steel was investigated in this work. Two types of wave excitation were used: broad band HSU-Nielsen source and artificial narrow band source via Vallen VS150-M transducer. AE responses were detected with use of 3 different AE transducers to take into account the effect of sensor transfer function on detected response. Attenuation curves were constructed from extracted amplitudes and digitalized signal was recorded for subsequent advanced analysis. Description of detected wave modes and separation of reflected waves was successfully done with use of combination of voltage-time dependency, wavelet transform (WT) and dispersion curves. Effect of wave propagation and transfer function of a sensor on signal maximum amplitude was discussed.
Highlights
acoustic emission (AE) is the phenomenon whereby transient elastic waves are generated by the rapid release of energy from localized sources within a material [1]
Typical continuous wavelet transform (CWT) and dispersion curves corresponding to measured signals from sensors B225.5, VS30V and VS45H in distance of 250mm from H-N source position are depicted on Fig. 6
Modes and frequencies corresponding to maximum amplitude and modes which vanish after some propagation distance are listed in Table 1 for sensors B225.5 and VS30V
Summary
AE is the phenomenon whereby transient elastic waves are generated by the rapid release of energy from localized sources within a material [1]. Employment of AE testing is diverse ranging from traditional industrial detection of defects in vessel and pipes to special applications with capability of source type classification, pharmaceutical applications, biologic and bionic applications, etc. Changing any of these dependencies will result in a different form of recorded signal from an identical source mechanism [3]. Results will serve as a reference for the following research considering signal classification in pressure vessel from same material type and wall thickness
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