Patent ID: 7496798
Filing Date: 2009-02-24
Classification: G05B

Abstract:
1. A data-centric monitoring method for detecting, isolating, and predicting abnormal conditions in a system comprising the steps of: a) acquiring measured data relating to at least one part or piece of the system; b) filtering bad or corrupt data; c) deriving a baseline for each monitored variable; d) calculating a residual from the baseline for each data point; e) calculating a trend line based on the residuals of each monitored variable; f) detecting data points whose residuals fall outside a normal operating limit for each monitored variable; g) detecting data points whose residuals violate one or several rules for abnormal conditions for each monitored variable; h) detecting any rapidly changing trend line slope or shape; i) issuing one or multiple alerts or warnings for any violations of the above; and j) consolidating multiple alerts or warning that correspond to the same cause into a single alert or warning of fault or faults; k) estimating the severity of each fault; l) estimating the effect of each fault on each system capability; m) analyzing each system capability variation of trend; n) extrapolating data along the trend line; o) detecting when data points will be outside operating limits; p) detecting when data points will violate abnormal condition rules; q) issuing one or multiple alerts or warnings for any detected violations of steps “o” and “p”; and r) consolidating multiple alerts or warning that correspond to the same cause into a single alert or warning; s) estimating fault severity and system capability over a future time window of interest.