Identification of different woody biomass for energy purpose by means of Soft Independent Modeling of Class Analogy applied to thermogravimetric analysis

In the renewable energy production solid biomass has became one of the most important source for power and heat generation, in particular woody materials in the form of wood chips, pellet and briquette. Technical standards on solid biofuels require information about origin and source of the biomass, differentiating for example between coniferous and broadleaf. In this work different wood samples were classified employing a method based on thermogravimetric analysis followed by Principal Component Analysis and Soft Independent Modeling of Class Analogy as supervised pattern recognition method.