Engine fault diagnosis using sound analysis

Vehicle engine faults are major faults which take place inside the engine of vehicle. Diagnosis of these faults is highly related to the technical expertise of the person and results in low success rates, so there is duly need of improving the diagnosing methods by improvising the innovative algorithms for faults diagnosis. A fault detection and diagnosis method for an engine's comprises of collecting a sensor signal from an acoustic of bike engine, extracting a feature set from the sensor signal using Mel-Frequency Cepstral Coefficients (MFCC) algorithms. Fault and non-fault states are reported based on comparison between the feature set and a library of fault and non-fault feature profiles corresponding to fault and non-fault states of the bike engine with inspected bike engine. In this paper we have presented the fault diagnosis method using the sound analysis by implementation of MFCC algorithm.