This paper presents an evaluation of some emerging techniques for gear fault detection based on vibration signal processing. These techniques acquire diagnostic information by processing the synchronously averaged signal using the continuous wavelet analysis, resonance demodulation and autoregressive (AR) modeling approaches. The evaluation results show that all three techniques are very promising for detecting and diagnosing localized gear faults, and are more effective than the traditional gear diagnostic techniques. Among the three techniques, the AR modeling method is probably the most promising one for implementation into an automated diagnostic system due to its effectiveness and simplicity in formulation.
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