Application of machine learning and soft computing techniques in monitoring systems' data analysis by example of dewater pumps monitoring system

Application of machine learning method for creation of equipment diagnostic model is presented in the paper. Dewater pump working in abyssal mining pump station has been chosen as the illustrative example. In the second section, dewater pumps monitoring system is presented, and necessity of the pump diagnostic model creation is justified. Next sections present application of data clustering algorithm and algorithm of decision trees induction. Methods of reduction the get diagnostic model is also developed. The reduction leads to more legible data models. Results of analysis done for two different type of pumps are presented in the last part of the paper.