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amuthakkannan rajakannu

National University of science and Technology,Oman

PO 2322, CPO 111, SEEB, MUSCAT, OMAN

SEEB, MUSCAT, OMAN

Muscat, Muscat 111

Oman

  • National University of science and Technology,Oman

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Scholarly Papers (1)

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Acoustic Emission-Based Intelligent Wear Detection for Spatiotemporal Data in Cnc Drill Bit Using Ceemdan for Feature Extraction and Convlstm for Fault Classification

Number of pages: 41 Posted: 29 May 2025
amuthakkannan rajakannu, Dr.Vijayalakshmi K., Sri Rajkavin AV and Jacob Wekalao
National University of science and Technology,Oman, affiliation not provided to SSRN, affiliation not provided to SSRN and University of Science and Technology of China (USTC)
Downloads 37 (1,263,436)

Abstract:

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Complete Ensemble Mode Decomposition with Adaptive Noise (CEEMDAN), convLSTM, Tool wear, Condition monitoring, Acoustic Emission Sensor, NI DAQ and LabVIEW