A real time detection of polymer type in polymeric materials using fluorescent properties and image processing technique

Identification of polymer type in unknown samples is an important issue in industry, which is accomplished using experimental methods such as spectrophotometric and microscopic methods, as well as measuring the physical and thermal characteristics of polymer. On the other hand, when it comes to industrial level and large sample sizes, aforementioned methods are laborious and costly. A common method to tackle the problem is to use chemical solvents and substances. Substantial use of chemicals, on the other hand, may lead to serious health and environmental issues. Therefore, the aim of this study is to introduce a promising clean, fast and facile approach in identification of polymeric materials that enables industry to bridge traditional process with predictive power of software tools. A special focus has been done on textile polymeric fibers and yarns. To address described issues, polymeric materials have been irradiated under ultraviolet (UV) light source. As a result, an augmented color difference appears between different polymer types, because of their different fluorescent activity. Created color difference was then, detected using a digital camera sensor, which works based on principals of image processing technique in python environment. Experimental observations showed good potential of using optical tools in polymer detection approaches.

Automated summary

Identification of polymer type is crucial in industry, but traditional methods are laborious and costly. This study introduces a clean and fast approach using optical tools to detect polymeric materials, focusing on textile fibers and yarns. Experimental observations show the potential of this method.