Bayesian Statistic Based Multivariate Gaussian Process Approach for Offline/Online Fatigue Crack Growth Prediction

Experimental Mechanics

Volumn 51, Issue 6, 2011, Pages 833-843

  Mohanty, S ^a   Chattopadhyay, A ^a   Peralta, P ^a   Das, S ^b  

^a ARIZONA STATE UNIVERSITY   (United States)

^b NASA AMES RESEARCH CENTER   (United States)

Author keywords

Fatigue life prediction; Gaussian process; Probabilistic approach; Statistical method; Structural health monitoring; Variable loading

Indexed keywords

FATIGUE LIFE PREDICTION; GAUSSIAN PROCESSES; PROBABILISTIC APPROACHES; STRUCTURAL HEALTH; VARIABLE LOADING; BAYESIAN STATISTICS; COMPACT TENSION; CRACK LENGTH; FATIGUE CRACKS; FATIGUE CYCLES; INPUT SPACE; LOAD RATIO; LOADING PARAMETERS; MAXIMUM LOAD; MINIMUM LOAD; MODEL INPUTS; MULTIVARIATE GAUSSIAN PROCESS; NONLINEAR FUNCTIONS; NUMERICAL EXAMPLE; OFFLINE; ONLINE PREDICTION; PIEZOELECTRIC SENSORS; PRINCIPAL COMPONENT ANALYSIS (PCA); REAL TIME; SENSOR SIGNALS; VARIABLE LOADINGS;

FATIGUE CRACK PROPAGATION; FATIGUE OF MATERIALS; FORECASTING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); LOADING; PRINCIPAL COMPONENT ANALYSIS; SENSORS; STOCHASTIC MODELS; STRUCTURAL HEALTH MONITORING; CRACKS;

CRACKS; LOADING;

EID: 79957919495     PISSN: 00144851     EISSN: 17412765     Source Type: Journal    
DOI: 10.1007/s11340-010-9394-7     Document Type: Article

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