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2020 | OriginalPaper | Buchkapitel

Neuro-Fuzzy Modeling and Wear Rate Predictions of Microwave Clads

verfasst von: Keerthana Chigateri, Ajit M. Hebbale, Baswanta S. Patil, M. Anjani Prasad

Erschienen in: Advances in Lightweight Materials and Structures

Verlag: Springer Singapore

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Abstract

SS-304 is extensively used in almost all industrial applications. Wear is one of the sever problems that reduce the life span of functional components. In the current work, an attempt is made to develop nickel-based clads though microwave energy at 900 W power. The developed clad shows excellent bonding with the target substrate without visible cracks. Microstructural and erosion analysis were carried out successfully. Taguchi L9 array was used with speed (S), impact angle (A) and various sizes of particles were considered for the erosion studies. The most reliable and popular neuro-fuzzy analytical technique was effectively used to forecast the wear behavior. Finally, the fuzzy predicted values were compared with experimentally obtained values. It was observed that the average percentage of error between fuzzy logic and experimental values is 10.34%.

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Metadaten
Titel
Neuro-Fuzzy Modeling and Wear Rate Predictions of Microwave Clads
verfasst von
Keerthana Chigateri
Ajit M. Hebbale
Baswanta S. Patil
M. Anjani Prasad
Copyright-Jahr
2020
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-7827-4_55

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