Radial basis and LVQ neural network algorithm for real-time fault diagnosis of bottle filling plant

Demetgül, MustafaYazıcıoğlu, OsmanKentli, Aykut2024-10-122024-10-1220141330-36511848-6339https://hdl.handle.net/11467/8777In this study, an Artificial Neural Network (ANN) is developed to find faults rapidly on a pneumatic system. The data were saved and evaluated considering system is working perfectly and faults are predetermined. These faults include having no bottle, a nonworking cap closing cylinder B, a nonworking bottle cap closing cylinder C, insufficient air pressure, water not filling and low air pressure faults. The signals of six sensors were collected during the entire sequence and the 18 most descriptive features of the data were encoded to present to the ANNs. Two different ANNs were applied for interpretation of the encoded signals. The ANNs tested in the study were learning vector quantization (LVQ) and radial basis network (RBN). The performance of LVQ and RBN was found to be fine with the presented procedures for a system having very repetitive sequential data.U ovom je radu razvijena umjetna neuronska mreža (ANN) za brzo pronalaženje grešaka na pneumatskom sustavu. Podaci su prikupljeni i procijenjeni smatrajući da sustav radi savršeno, a greške su unaprijed predviđene. Greške uključuju manjak boce, ne funkcioniranje cilindra B za stavljanje poklopca, neispravni cilindar C za stavljanje poklopca na boce, nedovoljan tlak zraka, voda se ne puni i nizak tlak zraka. Tijekom postupka prikupljeni su signali šest senzora te je za ANN kodirano 18 najkarakterističnijih obilježja podataka. Primijenjene su dvije različite umjetne neuronske mreže (ANN) za interpretaciju kodiranih signala. Umjetne neuronske mreže testirane u ispitivanju bile su "learning vector quantization (LVQ)" i "radial basis network (RBN)". Ustanovilo se da te dvije vrste umjetnih neuronskih mreža dobro funkcioniraju u primijenjenim postupcima u sustavu u kojem se sekvencijski podaci ponavljaju.eninfo:eu-repo/semantics/openAccessArtificial Neural NetworkBottle Filling PlantFault DiagnosisPneumaticDijagnoza GreškePneumatskiPogon Za Punjenje BacaUmjetna Neuronska MrežaRadial basis and LVQ neural network algorithm for real-time fault diagnosis of bottle filling plantAlgoritam radijalne osnove i LVQ algoritam neuronske mreže za pravovremenu dijagnozu greške pogona za punjenje bocaArticle214689695Q3WOS:000341262900001