Modelling of acrylic cut-pile carpet compression properties by means of expert systems based on carpet structural parameters

Abstract

Compression properties of carpet are a detrimental factor influencing carpet wear performance. In fact, carpet compression behavior determines carpet serviceability which in turn affects carpet appearance. Therefore, it is important to predict the carpet compression behavior in order to reduce the product cost. In this paper, a fuzzy logic model for prediction of compressional properties of acrylic cut-pile carpets is implemented in terms of the carpet structural parameters including carpet pile density, linear density of pile yarns and carpet pile height. In order to provide experimental data, six different acrylic cut-pile carpet samples fabricated by using six different acrylic spun pile yarns with yarn count of 18/3, 21/3, 27/3, 30/3, 33/3 and 36/3 Nm. Half of each provided carpet subjected to re-shearing process. All 12 carpet samples in two different cases (normal and reduced pile height) have been tested by standard carpet static and dynamic loading tests to measure thickness-loss as one of compression properties. Fuzzy logic model has been implemented and improved using genetic algorithm. Results show that correlation coefficients of model predictions with experimental values are 0.97, 0.98, 0.98 and 0.98 for carpet thickness-loss after low dynamic, high dynamic and static loading with short and long relaxation times, respectively. Also, linear regression trend between predicted and experimental values represented with a slope near to 1 and almost small bias (intercept). The result indicates that the developed fuzzy logic model is a reliable model predicting the acrylic cut-pile compression behavior.