Substructuring technique for damage detection using statistical multi-stage artificial neural network

Advances in Structural Engineering

Volumn 13, Issue 4, 2010, Pages 619-639

  Bakhary, Norhisham ^a   Hao, Hong ^b   Deeks, Andrew J ^b  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

^b UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

damage detection; multi stage artificial neural network; substructure

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CIVIL ENGINEERING STRUCTURES; COMPUTATIONAL EFFORT; COMPUTATIONAL TIME; COMPUTER MEMORIES; DAMAGE LOCATION; DEGREES OF FREEDOM; MATHEMATICAL METHOD; MODE SHAPES; MULTI-STAGE; NON-LINEAR; PROBABILISTIC METHODS; PROBABILITY METHODS; SMALL DAMAGE; STRUCTURAL DAMAGES; STRUCTURAL VIBRATION PROPERTIES; STRUCTURE MODELS; SUBSTRUCTURE; SUBSTRUCTURING TECHNIQUES; UNCERTAINTY EFFECTS; VIBRATION DATA; VIBRATION FREQUENCY;

CIVIL ENGINEERING; COMPUTATIONAL METHODS; COMPUTERS; CONCRETE BLOCKS; CONCRETE SLABS; MECHANICS; NEURAL NETWORKS; PROBABILITY DENSITY FUNCTION; STAGES; STRUCTURAL ANALYSIS; STRUCTURAL DYNAMICS; UNCERTAINTY ANALYSIS; VIBRATION ANALYSIS; VIBRATION MEASUREMENT;

DAMAGE DETECTION;

EID: 77955186372     PISSN: 13694332     EISSN: None     Source Type: Journal    
DOI: 10.1260/1369-4332.13.4.619     Document Type: Article

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