  Misfire in an IC Engine continues to be a problem leading to reduced fuel
efficiency, increased power loss and emissions containing heavy concentration
of hydrocarbons. Misfiring creates a unique vibration pattern attributed to a
particular cylinder. Useful features can be extracted from these patterns and
can be analyzed to detect misfire. Statistical features from these vibration
signals were extracted. Out of these, useful features were identified using the
J48 decision tree algorithm and selected features were used for classification
using the Kstar algorithm. In this paper performance analysis of Kstar
algorithm is presented.
