Classification of faults in motorcycles using signal processing and artificial intelligent techniques

Abstract

Motorcycle market is getting richer all over the world for its better mileage, smaller in size, lighter weight, less number of cylinder, less fuel consumption, style, modernization, innovation and easy to park. The motorcycle plays a very significant role in part time jobs among the youth for online delivery of food and other items. The motorcycle is preferred by the middle class people for its low cost transport. The motorcycles can be a cheap alternate source for public transportation during any pandemic situation. newlineDue to the increase in the motorcycle consumption, the fault diagnosis plays a major role in monitoring the condition of the motorcycle. To monitor the motorcycle faults more number of mechanic and more service stations are needed. Moreover, for identifying the faults at the initial condition before the motorcycle completely become damaged is very difficult. To diagnosis the faults in the inner portion of motorcycle engine such as cylinder, carburetor etc., it becomes more tedious, as the outer part of engines are need to be removed. It consumes more time and cost. To overcome all this issues, an automated method of fault recognition system is need to be developed newlineThe audio signal produced by the motorcycles are dissimilar for different working conditions. The emitted audio signals from the motorcycles are exploited as the information carrier to diagnose various faults in the motorcycle engine. This work is focused on the development of signal processing techniques and artificial intelligence techniques for the automatic detection and classification of faults based on the audio signals emitted by the motorcycle newline