Title :
A new spectrum distance function to monitor machine condition
Author_Institution :
Coll. of Econ. & Adm., China Jiliang Univ., Hangzhou, China
Abstract :
This paper proposes a new distance function - power spectral density divergence to monitor machine condition .The distance function carries full information of time series model ARMA (m, n). The calculating example shows that it is more sensitive than I-divergence, J-divergence, and Bhattcharyya information distance to the changes of machine conditions.
Keywords :
condition monitoring; machinery; signal processing; time series; vibrations; Bhattcharyya information distance; machine condition monitoring; spectrum distance function; time series model; time series signal; vibration signal; distance; machine condition; monitor; power spectral density divergence; time series;
Conference_Titel :
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-7957-3
DOI :
10.1109/CMCE.2010.5610500
