The Use of the Visualisation of Multidimensional Data Using PCA to Evaluate Possibilities of the Division of Coal Samples Space Due to their Suitability for Fluidised Gasification

摘要

Methods serving to visualise multidimensional data through the transformation of multidimensional?space into two-dimensional space, enable to present the multidimensional data on the computer screen.?Thanks to this, qualitative analysis of this data can be performed in the most natural way for humans,?through the sense of sight. An example of such a method of multidimensional data visualisation is PCA?(principal component analysis) method. This method was used in this work to present and analyse a set?of seven-dimensional data (selected seven properties) describing coal samples obtained from Janina?and Wieczorek coal mines. Coal from these mines was previously subjected to separation by means of?a laboratory ring jig, consisting of ten rings. With 5 layers of both types of coal (with 2 rings each) were?obtained in this way. It was decided to check if the method of multidimensional data visualisation enables?to divide the space of such divided samples into areas with different suitability for the fluidised gasification?process. To that end, the card of technological suitability of coal was used (Sobolewski et al., 2012;?2013), in which key, relevant and additional parameters, having effect on the gasification process, were?described. As a result of analyses, it was stated that effective determination of coal samples suitability?for the on-surface gasification process in a fluidised reactor is possible. The PCA method enables the?visualisation of the optimal subspace containing the set requirements concerning the properties of coals?intended for this process.