Detection of an Approximately Periodic Sequence of Pulses for Acoustic Condition Monitoring

Acoustic condition monitoring is a cost-effective approach to maintain proper machine operation. Defective machines often generate knocking sounds, e.g., due to loose metal parts, which can be modelled as an approximately periodic sequence of acoustic pulses. Based on a signal model for these sequential pulses, we derive a z-transform-based maximum a posteriori ratio test (MAPRT) detector that reliably detects such knocking noises. The proposed detector is tested with measurement data showing that it is more robust than the commonly used generalized likelihood ratio test (GLRT) pitch detector. Furthermore, the proposed MAPRT detector can be implemented efficiently using the chirp z-transform.