Abstract: A method of analyzing vibrations of a rolling element bearing installed in a rotating machine includes accessing vibration data corresponding to the bearing to be analyzed, determining a degraded condition factor BD for the bearing, selecting an expected designer-determined mean-time-to-failure MTTF of the bearing operating under a design load in the operating environment of the rotating machine, selecting a forecast time period, calculating a reduced mean-time-to-failure RMTTF of the bearing using the expected designer-determined mean-time-to-failure MTTF and the degraded condition factor BD, calculating a probability of failure of the bearing in the forecast time period using the reduced mean-time-to-failure RMTTF, accessing cost data corresponding to a cost of failure of the bearing in the rotating machine, calculating a financial risk from the calculated probability of failure in the forecast time period and the cost data, and displaying the financial risk for the selected time period.

Abstract: A method of analyzing vibrations of a rolling element bearing installed in a rotating machine includes accessing vibration data corresponding to the bearing to be analyzed, determining a degraded condition factor BD for the bearing, selecting an expected designer-determined mean-time-to-failure MTTF of the bearing operating under a design load in the operating environment of the rotating machine, selecting a forecast time period, calculating a reduced mean-time-to-failure RMTTF of the bearing using the expected designer-determined mean-time-to-failure MTTF and the degraded condition factor BD, calculating a probability of failure of the bearing in the forecast time period using the reduced mean time to failure RMTTF, accessing cost data corresponding to a cost of failure of the bearing in the rotating machine, calculating a financial risk from the calculated probability of failure in the forecast time period and the cost data, and displaying the financial risk for the selected time period.

Abstract: The Multiple Discriminant Analysis system described provides three parameters: (1) a Dynamic Force Factor (DFF) that characterizes the dynamic forces which act to reduce operational life of the bearing; (2) a Bearing Degradation Factor (BDF) that characterizes the actual condition of the rolling element bearing; and (3) a Life Expectancy Factor (LEF) that characterizes the overall condition of the first two factors. Each factor is configured in scalar form, wherein readings range from acceptable, to caution/degradation, to action required. DFF combines low frequency and high frequency dynamic forcing function discriminants. BDF combines, in this case, four powerful diagnostic bearing fault process discriminants, in a formulaic composition. The composition accurately describes the actual rolling element bearing condition indicating optimum or warning of a potential failure condition. The normally voluminous vibration data is compressed into three easily understood, yet highly informative numbers.