Fuzzy condition monitoring of recirculation fans and filters

Abstract

A reliable condition monitoring is needed to predict faults. Pattern recognition technologies are often used for finding patterns in complex systems. Condition monitoring can also benefit from pattern recognition. Many pattern recognition technologies, however, only output the classification of the data sample but do not output any information about classes that are also very similar to the input vector. This paper presents a concept for pattern recognition that output similarity values for decision trees. The concept can be used on top of any normal decision tree algorithms and is independent of the learning algorithm. Performed experiments showed that the concept is reliable and it also works with decision tree forests to increase the classification accuracy.