Optimum parameters for fault detection and diagnosis system of batch reaction using multiple neural networks

Journal of Loss Prevention in the Process Industries

Volumn 25, Issue 1, 2012, Pages 138-141

  Tan, W L ^a   Nor, N M ^a   Abu Bakar, M Z ^a   Ahmad, Z ^a   Sata, S A ^a  

^a SCHOOL OF PHYSICS   (Malaysia)

Author keywords

Batch; Diagnosis system; Fault; Multiple neural networks

Indexed keywords

BATCH; BATCH CHEMICAL REACTORS; BATCH PROCESS; BATCH REACTIONS; CONTINUOUS PROCESS; DATA VALIDATION; DIAGNOSIS SYSTEM; EARLY DETECTION; FAULT; FAULT DETECTION AND DIAGNOSIS SYSTEMS; FAULTY CONDITION; HIDDEN LAYERS; MINIMAL ERRORS; MULTI-LAYER FEED FORWARD; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; MULTIPLE NEURAL NETWORKS; OPTIMUM NETWORKS; OPTIMUM PARAMETERS; PROCESS PARAMETERS; TIME VARYING;

ACETIC ACID; BATCH DATA PROCESSING; CHEMICAL REACTORS; ETHANOL; FAULT DETECTION; NETWORK ARCHITECTURE; NETWORK LAYERS; STRUCTURES (BUILT OBJECTS); SULFURIC ACID; TIME VARYING NETWORKS;

NEURAL NETWORKS;

EID: 83255176824     PISSN: 09504230     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jlp.2011.08.002     Document Type: Article

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