Title :
Online detection of fatigue failure via symbolic time series analysis
Author :
Gupta, Shalabh ; Ray, Asok ; Keller, Eric
Author_Institution :
Pennsylvania State Univ., University Park, PA, USA
Abstract :
This paper examines the efficacy of symbolic-time series analysis for online detection of fatigue failure in mechanical structures. The detection algorithm is formulated on the principles of symbolic dynamics and automata theory. The performance of this method is evaluated based on the information extracted from available sensor data for early detection of small anomalies in the observed data sequence. This concept is experimentally validated on a fatigue damage test apparatus. The time series data, generated from ultrasonic sensor and optical microscope, have been used for detection of small fatigue crack growth in ductile alloy 7075-T6 aluminium specimens.
Keywords :
automata theory; failure (mechanical); failure analysis; fatigue; fatigue testing; structural engineering; time series; automata theory; fatigue crack; fatigue damage test apparatus; fatigue failure; information extraction; mechanical structures; online detection; optical microscope; symbolic time series analysis; ultrasonic sensor; Automata; Data mining; Detection algorithms; Failure analysis; Fatigue; Mechanical sensors; Optical microscopy; Optical sensors; Testing; Time series analysis;
Conference_Titel :
American Control Conference, 2005. Proceedings of the 2005
Print_ISBN :
0-7803-9098-9
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2005.1470481
