Frequency selection with oscillatory neurons for engine misfire detection

Engine misfire detection is one of the great issues in automobile systems to inform incomplete engine exhaustion which causes environmental problem and also to guarantee safe operation of the vehicles. It requires continuous monitoring of the system in real-time to detect deviations from the normal signal patterns. This paper presents a special frequency selection method based on recurrent neural networks consisting of oscillatory neurons, and applies the method with the genetic algorithm to engine misfire detection problem by observing the engine speed in an automobile system.