생산 공정에서 CNN을 이용한 음향 PSD 영상 기반 공구 상태 진단기법.

Autor: 이경민
Předmět:
Zdroj: Journal of the Korea Institute of Information & Communication Engineering; Jul2022, Vol. 26 Issue 7, p981-988, 8p
Abstrakt: The intelligent production plant called smart factories that apply information and communication technology (ICT) are collecting data in real time through various sensors. Recently, researches that effectively applying to these collected data have gained a lot of attention. This paper proposes a method for the tool condition monitoring based on the sound signal generated in machining process. First, it not only detects a fault tool, but also presents various tool states according to idle and active operation. The second, it's to represent the power spectrum of the sounds as images and apply some transformations on them in order to reveal, expose, and emphasize the health patterns that are hidden inside them. Finally, the contrast-enhanced PSD image obtained is diagnosed by using CNN. The results of the experiments demonstrate the high discrimination potential afforded by the proposed sound PSD image + CNN and show high diagnostic results according to the tool status. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index