Degradation process prediction for rotational machinery based on hybrid intelligent model

Robotics and Computer-Integrated Manufacturing

Volumn 28, Issue 2, 2012, Pages 190-207

  Du, Shichang ^a   Lv, Jun ^b   Xi, Lifeng ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

Ball bearing; Degradation process monitoring; Neural network ensemble; Vibration

Indexed keywords

DEGRADATION PROCESS; DEGRADATION PROCESS MONITORING; EXPERIMENTAL SETUP; GENERALIZATION PERFORMANCE; HYBRID INTELLIGENT MODEL; IMPROVED PARTICLE SWARM OPTIMIZATION; LOCAL OPTIMA; NEURAL NETWORK ENSEMBLE; NEURAL NETWORK ENSEMBLES; OPTIMAL SUBSETS; PREDICTION MODEL; PREDICTIVE MAINTENANCE;

BALL BEARINGS; COMPUTER SIMULATION; DEGRADATION; FATIGUE TESTING; FORECASTING; MACHINERY; MATHEMATICAL MODELS; PARTICLE SWARM OPTIMIZATION (PSO); PROCESS MONITORING; SIMULATED ANNEALING;

NEURAL NETWORKS;

EID: 80055081674     PISSN: 07365845     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rcim.2011.08.006     Document Type: Article

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