Fault detection in internal combustion engines using fuzzy logic

In this study, a complementary fuzzy-logic-based fault diagnosis system was developed to diagnose the faults of an internal combustion engine (ICE) and the system incorporated with an engine test stand. The input variables of the fuzzy logic classifier were acquired via a data acquisition card and RS-232 port. The rule base of this system was developed by considering the theoretical knowledge, the expert knowledge, and the experiment results. The accuracy of the fuzzy logic classifier was tested by experimental studies which were performed under different fault conditions. Using the developed fault diagnosis system, ten general faults which were observed in the internal combustion engine were successfully diagnosed in real time. With these characteristics, the system could easily be used for fault diagnosis in test laboratories and in service workshops.