Application of Neural network for fault diagnosis of cracked cantilever beam

2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings

Volumn , Issue , 2009, Pages 1303-1308

  Das, H C ^a   Parhi, Dayal R ^b  

^a SIKSHA O ANUSANDHAN DEEMED TO BE UNIVERSITY   (India)

^b NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Beam; Crack; Mode shape; Natural frequency; Neural network; Stiffness; Strain energy; Stress intensity factor; Vibration

Indexed keywords

BEAM; CLOSE PROXIMITY; CRACK DEPTHS; CRACK LOCATION; CRACK MODE; DIFFERENT BOUNDARY CONDITION; EXPERIMENTAL SETUP; FAULT DIAGNOSIS; INPUT PARAMETER; MODE SHAPE; MODE SHAPES; NEURAL NETWORK SYSTEMS; NEURAL NETWORK TECHNIQUES; OUTPUT PARAMETERS; RELATIVE DEVIATIONS; THEORETICAL EXPRESSION; TRAINING PATTERNS;

ASPHALT PAVEMENTS; ATOMIC FORCE MICROSCOPY; CANTILEVER BEAMS; CRACK PROPAGATION; CRACKS; FAILURE ANALYSIS; LOCATION; NANOCANTILEVERS; NATURAL FREQUENCIES; PILE FOUNDATIONS; STIFFNESS; STRAIN ENERGY; STRAIN RATE; STRESS INTENSITY FACTORS;

NEURAL NETWORKS;

EID: 77949650464     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NABIC.2009.5393733     Document Type: Conference Paper

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