Open AccessAnalysis of Regenerative Raw Signals Using Variational Mode Decomposition
Author(s) -
Yogesh Shrivastava,
Eram Neha,
Bhagat Singh,
P. K. Shrivastava,
K.V.S.R. Murthy,
Durgesh Nandan
Publication year - 2022
Publication title -
traitement du signal/ts. traitement du signal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.279
H-Index - 11
eISSN - 1958-5608
pISSN - 0765-0019
DOI - 10.18280/ts.390131
Subject(s) - microphone , mode (computer interface) , frequency domain , machining , computer science , frequency response , control theory (sociology) , time domain , engineering , algorithm , artificial intelligence , mechanical engineering , computer vision , telecommunications , electrical engineering , control (management) , sound pressure , operating system
Faults like regenerative tool chatter have been evaluated by several researchers in order to suppress its adverse effect. However, many facets of this domain are yet to be addressed. In the present work, a new methodology has been proposed to process the recorded regenerative chatter signals in order to extract the chatter features. In the proposed approach, experiments have been performed and signals pertaining to regenerative tool chatter have been recorded using microphone. Thereafter, the recorded signals have been evaluated and preprocessed using variational mode decomposition (VMD) in order to extract chatter features. The decomposed signals that result in variational mode functions have been further evaluated by calculating a response termed as chatter index. This response has been used to predict the chatter severity during machining at different combinations of input parameters, on verifying the obtained results it has been found that the proposed methodology is significant in identifying the chatter severity.