Abstract
This paper was according to the early crack identification on metal deep drawing, combined with the characteristics of the AE singal of deep drawing forming, determined to analyze it by db4 wavelet basis function for 3 layers, extracted the energy value at every point of the eight AE signal samples from deep drawing forming which crack state was known to constituted characteristic matrix, fuzzy equivalence matrix was obtained by a series of matrix transformation,which was regard as pattern library of crack that used in cluster analysis. Then extracted energy value at every point of AE signal from deep drawing experiments with there states unknown, calculate similarity between samples and the model we established by using euclidean distance formula after normalization processing, deep drawing state was determined by the principle of selecting near, finally compared the recognition result with crack situation deviced by naked eye and microscope, results show that the accuracy of fuzzy identification of early crackn based on fuzzy clustering is up to 90%.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
