Industrial application for inline material sorting using hyperspectral imaging in the NIR range

Abstract

Spectral imaging is becoming increasingly interesting not only for agricultural use but also for industrial applications. Wavelengths in the near infrared (NIR) range, in particular, can be used for materials classification. However, sorting paper according to quality is a very difficult task due to the close similarities between the materials. This work describes the development of a unique industrial inline material sorting system which uses the spectral imaging technique. The main functional parts and the sensor unit are described in detail. Classification methods for cellulose-based materials such as pulp, paper and cardboard will be discussed, as will hardware requirements for the industrial use of spectral imaging solutions, including adjustment and calibration techniques. The description of the software design focuses on the classification speed required.