A fault detection and diagnosis method for a gas turbine engines comprises collecting a sensor signal from an acoustic or vibrational sensor at the gas turbine engine, pre-processing the sensor signal to remove predictable background, and extracting a feature set from the sensor signal using Mel-Frequency Cepstral Coefficients (MFCC) algorithms and/or Code Excited Linear Prediction (CELP) 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 gas turbine engine.