Banana-Glass Fiber Composite for Acoustic Insulation and Prediction of Its Properties by Fuzzy Logic System

Abstract

The objective of the current study is to develop a model employing a fuzzy logic expert system (FLES) for predicting the noise reduction coefficient (NRC) of a banana-glass fiber composite. Banana fiber has a strong ability to muffle sounds while having low tensile strength. Glass fiber, on the other hand, has a limited capacity for sound absorption despite having considerable tensile strength. A composite consisting of banana and glass fiber has been developed in order to increase noise reduction capability while keeping appropriate tensile strength. The sound adsorption test was done by passing sound through composites via an impedance tube. It was found that 25% banana and 75% glass hybrid composite having 5 mm thickness shows 375.96% more NRC than 100% glass fiber composite. Only a 25% increase of banana fiber content increased NRC incredibly. Different compositions of glass fiber, banana fiber, and thicknesses of the composites were taken as the input variables and the output, noise reduction coefficient. To better comprehend the relationship between these variables, a fuzzy logic-based model was created and the model’s coefficient of determination (R2) was found to be 0.9884. The model accurately anticipated the noise reduction coefficient of the composites with varying constituent percentages and thicknesses.

Keywords

• natural fiber
• synthetic fiber
• hybrid composite
• tensile strength
• noise reduction coefficient (nrc)
• fuzzy logic system