Time Domain Analysis

Vibration signals collected from a rotating machine using vibration transducers are often in the time domain. The manual inspection of vibration signals as part of time domain fault diagnosis maybe divided into two main types: visual inspection and feature-based inspection. This chapter introduces vibration signal processing in the time domain by giving an explanation of statistical functions and other advanced techniques that can be used to extract features from time-indexed raw vibration datasets, which sufficiently represent machine health. The advanced techniques include: time synchronous average, autoregressive moving average, filter-based methods, stochastic parameter techniques, and blind source separation. Numerous types of statistical functions have been heavily used to extract features from vibration signals in the time domain based on signal amplitude. Model-based techniques for vibration monitoring can provide a means of detecting machine faults even if data are only available from the machine in its normal condition.