Title :
Utilization of information maximum for condition monitoring with applications in a Machining Process and a water pump
Author :
Li, Xiaoli ; Du, R. ; Guan, X.-P.
Author_Institution :
Sch. of Comput. Sci., Univ. of Birmingham, UK
Abstract :
This work presents a new method for the condition monitoring based on the so-called information maximum (InfoMax). First, the InfoMax concept is employed to build a neural network. The neural network is used for independent component analysis to identify the source (input) that causes malfunctions (output). To demonstrate the new method, two application examples were included. First, tool breakage detection in an end milling process. The monitoring signal is the current of the feed-motor, which is used to detect the change of the cutting force and accordingly, to detect tool breakage. Second, is the monitoring of a water pump. In this example, seven acceleration signals were simultaneously acquired and used to identify the location of the fault (bearing crack). The experiment results indicate that the new method is effective.
Keywords :
condition monitoring; independent component analysis; milling; neural nets; production engineering computing; pumps; condition monitoring; end milling process; feedmotor; independent component analysis; information maximum; machining process; neural networks; water pump; Acceleration; Condition monitoring; Entropy; Independent component analysis; Machining; Milling; Mutual information; Neural networks; Pumps; Rotating machines; Condition monitoring; end milling; independent component analysis; information maximum (InfoMax); pump;
Journal_Title :
Mechatronics, IEEE/ASME Transactions on
DOI :
10.1109/TMECH.2004.839032