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Condition-Aware Autoencoder and Transfer Learning-Based Estimation of Milling Cutting Forces from Spindle Vibration Signals
Machines 교신저자 20250527 -
Physically-based constitutive model and dynamic recrystallization behavior of AISI 4330V mod. Alloy steel under hot working conditions
Journal of Materials Research and Technology-JMR&T 제2저자 20250507 -
Cutting Force Estimation Using Milling Spindle Vibration-Based Machine Learning
Applied Sciences-Basel 교신저자 20250301 -
Nozzle Condition Monitoring System Using Root Mean Square of Acoustic Emissions during Abrasive Waterjet Machining
Journal of Manufacturing and Materials Processing 교신저자 20220401 -
연마재 워터젯을 위한 노즐상태 모니터링 시스템 설계
한국산업융합학회논문집(JOURNAL OF THE KOREAN SOCIETY OF INDUSTRY CONVERGENCE) 참여저자 20201031