In the past twenty years, impulse excitation technique (IET) has become a widely diffused non-destructive technique in metal industry field. This success resides in its capability to determine with high precision and accuracy some elastic properties of materials, such as Young’s modulus, shear modulus and Poisson’s ratio. The technique, which is very fast and non-destructive, consists in exciting a sample by a mechanical input and registering the acoustic output that, once analyzed by Fast Fourier-Transformation (FFT), provides the resonant frequencies of the sample, with a fast data analysis procedure. The approach is thus very easy to be applied to most materials and cost and time effective. Despite these many advantages, IET is still an under exploited technique in academic research centres, that mainly rely on traditional destructive methods for the evaluation of such properties, for instance by the measurement of strain-stress curves. Commercial IET instruments, similarly to traditional ones, have costs spanning from many hundreds to thousands of dollars, limiting their diffusion in academic world but also in small companies with limited R&D or quality control expenses. Non-professional instruments can also give very precise results and can be successfully used in basic research and in quality control even if not certified as commercial ones. Moreover they can be easily customized according to specific user needs and sample features. Since no examples of low cost IET designs can still be found in the scientific literature, we fill the gap in this paper, giving instructions for a self-assembled instrument for IET analysis, with a cost in the range of 70–85 USD. Moreover, the collected calibration data are analyzed to prove that the instrument can be used for other purposes than the common elastic properties determination, but also for a fast and cheap material characterization exploiting a multivariate analysis approach. Calibration results show that IETeasy can be used in both academic and industrial field for quality control purposes as a low-cost, fast and efficient alternative to tensometers. Principal component analysis, applied in this paper for the first time to IET data analysis, was able to distinguish and classify steel from Al or Cu alloys from polymers, but also different steel grades, demonstrating its potential in massive and eventually automatic IET data analysis. Calculated mechanical properties fitted with good approximation the ranges expected for each sample.
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