Blade material fatigue assessment using Elman Neural Networks

ASME International Mechanical Engineering Congress and Exposition, Proceedings

Volumn 14, Issue , 2008, Pages 59-64

  Jihong, Yan ^a   Pengxiang, Wang ^b  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b University of Wisconsin Milwaukee   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ACQUISITION; ELECTRIC POWER PLANTS; FATIGUE DAMAGE; ROTORS; STEAM TURBINES; TURBOMACHINE BLADES; DAMAGE DETECTION; FATIGUE OF MATERIALS; FORECASTING; RECURRENT NEURAL NETWORKS; RELIABILITY ANALYSIS; REPAIR; RISK ANALYSIS; RISK ASSESSMENT; SAFETY ENGINEERING;

BLADE MATERIAL FATIGUE ASSESSMENT; ELMAN NEURAL NETWORKS; FATIGUE SEVERITY ASSESSMENT; MATERIAL DEGRADATION EVALUATION; CONTINUOUS OPERATION; DAMAGE PROPAGATION; ELMAN NEURAL NETWORK; LIFE PREDICTIONS; MATERIAL DEGRADATION; MATERIAL TESTING SYSTEMS; ROBUST MATERIALS; TREND PREDICTION;

RECURRENT NEURAL NETWORKS; FATIGUE DAMAGE;

EID: 44349171065     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/IMECE2007-43311     Document Type: Conference Paper

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