The rotating machinery features describe aspects of gearbox machinery, where one master shaft drives other rotating gears. The system is harmonically interrelated, and this interrelationship allows metrics that can not only detect, but also locate the source of the fault.
The statistical rotating machinery features are similar in nature to their general statistical counterparts in Signal Statistics. The remaining features were derived through research in the literature, and empirically determined to be effective for differentiating or isolating specific types of faults.
TSA Signal — A time-synchronous averaged (TSA) signal is essential to calculating rotating machinery features. To generate a TSA signal, use Filtering & Averaging > Time-Synchronous Signal Averaging.
Difference Signal, Regular Signal — These filtered TSA signals provide the source for the specialized rotating machinery metrics. To generate these signals, use Filtering & Averaging > Filter Time-Synchronous Signal Averaged Signals.
Root Mean Square (RMS) — Indication of the overall condition of the gearbox
Kurtosis — Indication of major peaks in the signal
Crest Factor (CF) — Peak-to-RMS ratio, which is an indication of gear damage in its early stages, especially where vibration signals exhibit impulsive traits
Kurtosis (FM4) — Detect faults isolated to only a limited number of teeth in a gear mesh
Normalized 6th moment (M6A) — Indication of surface damage on the rotating machine components
Normalized 8th moment (M8A) — An improved version of the
Zero-order figure of merit (FM0) — Ratio of the standard deviations of the difference and regular signals, which is an indication of heavy wear and tooth breakage
Energy Ratio (ER) — Indication of heavy uniform wear, where multiple teeth on the gear are damaged
The software stores the results of the computation in new features. The new feature
names include the source signal name with the suffix
For information on using these metrics for evaluating rotating machinery, see Condition Indicators for Gear Condition Monitoring. For information on
specific rotating metrics, see