Indian Journal of Engineering & Materials Sciences

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


Affiliations
1 Jaypee University of Engineering and Technology, Guna (M.P.), 473 226, India
2 Galgotias College of Engineering and Technology, Greater Noida 201 310, India
 

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.

Keywords

Chatter, Grey Relational Analysis, Local Mean Decomposition, Wavelet Denoising.
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Abstract Views: 85

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  • Comparison of Signal Processing Techniques for Prediction of Optimal Process Variables to Yield Higher Productivity during Turning on CNC Lathe

Abstract Views: 85  |  PDF Views: 54

Authors

Pankaj Gupta
Jaypee University of Engineering and Technology, Guna (M.P.), 473 226, India
Bhagat Singh
Galgotias College of Engineering and Technology, Greater Noida 201 310, India
Yogesh Shrivastava
Jaypee University of Engineering and Technology, Guna (M.P.), 473 226, India

Abstract


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.

Keywords


Chatter, Grey Relational Analysis, Local Mean Decomposition, Wavelet Denoising.

References