Pump Failure Detection using Support

For good classiication preprocessing is a key step. Good pre-processing reduces the noise in the data and retains most information needed for classiication. Poor preprocessing on the other hand can make classiication almost impossible. In this paper we evaluate several feature extraction methods in a special type of outlier detection problem, machine fault detection. We will consider measurements on water pumps under both normal and abnormal conditions. We use a novel data description method, called the Support Vector Data Description, to get an indication of the complexity of the normal class in this data set and how well it is expected to be distinguishable from the abnormal data.