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Content available remote The location of anomalous spikes on a working rotor: a theorical-experimental test
EN
An efficient and efficacious response to the continuous request of "high performance", in terms of qualitative standards, becomes one of the most important factors in determining the profit of a business. The aim of this paper is to check the reliability of a signal analysis method based on a Discrete Wavelet Transform (DWT). This algorithm appears useful in revealing anomalies that are added to a regular signal. Such anomalies, characterized by high frequency, small amplitude and short period, generally are filtered in a data logging or sampling. Moreover, it has been illustrated how, for each level of the DWT, the maximum value of the entropy allows the location as well as the best graphical representation of the phenomenon in study. In this paper the results obtained during the functioning of an experimental equipment will be shown.
EN
The system achieved is an integration of the identification system, we planned and carried out, as we previously described (Niola et al., 1999). From the depth map onwards, that is the output of the identification system, the classification system, operating on the single lines of the map, reconstructs through interpolation the level lines of the image, which are to be fitted to Fuzzy set; in order to do this, a mixed neuro-fuzzy technique is adopted. The so achieved input Fuzzy sets, level lines that have been modelled, are compared to the output Fuzzy sets, which reproduce a parameterisation of the defect according to its depth, by means of inference rules planned on purpose. The final result will give a quantification of the defect found, besides pointing out the area in which it has been noticed.
EN
We have worked out an innovative system for the identification of superficial defects in low critical metallic patches. In a few seconds we reconstruct, using the fundamental principles of shape from shading, the third dimension of a digitized image, thanks to which we can identify the presence of a defect. Testing shows that the results achieved are more than satisfactory also in relation to the good rejection of the noises from the algorithm. Moreover we propose the advantages of using this system in an industrial field, and the conditions to be verified in industry in order to be able to test this technique.
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