Open AccessResearch and application on rapid recognition of CNC machine tools’ running state
Author(s) -
Mengmei Li,
Yuanmeng Xia,
Xuezhen Chen
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/793/1/012064
Subject(s) - numerical control , computer science , domain (mathematical analysis) , state (computer science) , identification (biology) , correlation coefficient , machine tool , artificial intelligence , pattern recognition (psychology) , machine learning , algorithm , engineering , mathematics , mechanical engineering , mathematical analysis , botany , biology , machining
A rapid recognition of CNC (Computer Numerical Control) machine tools’ running state based on time domain characteristic parameters and frequency domain correlation coefficient was proposed. The experiment proved the accuracy and efficiency of the mentioned method, which made the states recognition rate reach 93.33% and the identification efficiency improve 66.67%. In this scenario, a theoretical foundation is established for the condition-based maintenance of CNC machine tools.