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Comparison of Signal Processing Techniques for Prediction of Optimal Process Variables to Yield Higher Productivity During Turning on CNC lathe

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Title Comparison of Signal Processing Techniques for Prediction of Optimal Process Variables to Yield Higher Productivity During Turning on CNC lathe
 
Creator Gupta, Pankaj
Singh, Bhagat
Shrivastava, Yogesh
 
Subject Chatter
Grey relational analysis
Local mean decomposition
Wavelet Denoising
 
Description 103-111
Tool chatter is one of such occurrences that limits MRR in a number of industries. In the current research, a method to
boost output while lowering clatter during turning operations on a CNC lathe has been presented. A microphone is used to
record the vibration signals generated during turning tests. The denoised signals are analysed using local mean
decomposition (LMD). Disruptions and undesirable embedded ambient noise are removed using wavelet denoising (WD).
The product functions that expose chatter information are chosen using these decomposed signals. To recreate the real-time
chatter, these well-known PFs are used to reconstruct the signal. A consistent range of turning parameters for greater
productivity has been created using the Grey relational analysis (GRA) prediction technique. The measured Chatter Index
value has been found to denote steady turning, unstable, and moderate chatter circumstances. In order to confirm the validity
of the presented methodology, several tests have been conducted.
 
Date 2023-03-06T11:17:20Z
2023-03-06T11:17:20Z
2023-03
 
Type Article
 
Identifier 0971-4588 (Print); 0975-1017 (Online)
http://nopr.niscpr.res.in/handle/123456789/61499
https://doi.org/10.56042/ijems.v1i1.48945
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source IJEMS Vol.30(1) [February 2023]