Patent Number: 056298722
Section: summary

The present invention is concerned generally with a system and method for reliably monitoring industrial processes having nonwhite noise characteristics. More particularly, the invention is concerned with a system and method for removal of nonwhite noise elements or serially correlated noise, allowing reliable supervision of an industrial process and/or operability of sensors monitoring the process. Conventional parameter-surveillance schemes are sensitive only to gross changes in the mean value of a process, or to large steps or spikes that exceed some threshold limit check. These conventional methods suffer from either large numbers of false alarms (if thresholds are set too close to normal operating levels) or a large number of missed (or delayed) alarms (if the thresholds are set too expansively). Moreover, most conventional methods cannot perceive the onset of a process disturbance or sensor deviation which gives rise to a signal below the threshold level for an alarm condition. In another conventional monitoring method, the Sequential Probability Ratio Test ("SPRT") has found wide application as a signal validation tool in the nuclear reactor industry. Two features of the SPRT technique make it attractive for parameter surveillance and fault detection: (1) early annunciation of the onset of a disturbance in noisy process variables, and (2) the SPRT technique has user-specifiable false-alarm and missed-alarm probabilities. One important drawback of the SPRT technique that has limited its adaptation to a broader range of nuclear applications is the fact that its mathematical formalism is founded upon an assumption that the signals it is monitoring are purely Gaussian, independent (white noise) random variables. It is therefore an object of the invention to provide an improved method and system for continuous evaluation and/or modification of industrial processes and/or sensors monitoring the processes. It is another object of the invention to provide a novel method and system for statistically processing industrial process signals having virtually any form of noise signal. It is a further object of the invention to provide an improved method and system for operating on an industrial process signal to remove unwanted serially correlated noise signals. It is still an additional object of the invention to provide a novel method and system utilizing a pair of signals to generate a difference function to be analyzed for alarm information. It is still a further object of the invention to provide an improved method and system including at least one sensor for providing a real signal characteristic of a process and a predicted sensor signal allowing formation of a difference signal between the predicted and real sisal for subsequent analysis free from nonwhite noise contamination. It is also an object of the invention to provide a novel method and system wherein a difference function is formed from two sensor signals, and/or pairs of signals and nonwhite noise is removed enabling reliable alarm analysis of the sensor signals. It is yet an additional object of the invention to provide an improved method and system utilizing variable pairs of sensors for determining both sensor degradation and industrial process status. Other objects, features and advantages of the present invention will be readily apparent from the following description of the preferred embodiments thereof, taken in conjunction with the accompanying drawings described below.