The Condition Monitoring and Performance Evaluating of Digital Manufacturing Process

Authors:
Xuefeng Chen;Bing Li;Hongrui Cao;Zhengjia He
Affiliations:
State Key Lab. for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, PRC 710049;State Key Lab. for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, PRC 710049;State Key Lab. for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, PRC 710049;State Key Lab. for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, PRC 710049
Venue:
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part II
Year:
2008

Citing 3
Cited 0

A basis for efficient representation of the S-transform

Digital Signal Processing
Localization of the complex spectrum: the S transform

IEEE Transactions on Signal Processing
The inverse S-transform in filters with time-frequency localization

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Spindle assembly is one of the most important components of digital manufacturing equipments. It is key problem to monitor and evaluate its performance to assure the normal process. Aiming at the bearings which damage most easily in spindle system, a new time-frequency analysis method called S transform is studied, time-frequency distribution of vibration signals collected from spindle is obtained, and a singular value decomposition method is employed to condense the time-frequency matrix data so that the fault features can be extracted quantitatively. Simulation and experimental studies have demonstrated that the proposed method may identify the running state of spindle bearing accurately. Thus a new technique for the evaluation of spindle serving performance of digital manufacturing equipments is provided.