Data processing: generic control systems or specific application – Generic control system – apparatus or process – Optimization or adaptive control
Reexamination Certificate
1998-02-24
2001-01-30
Gordon, Paul P. (Department: 2786)
Data processing: generic control systems or specific application
Generic control system, apparatus or process
Optimization or adaptive control
C700S028000, C700S047000, C700S048000, C700S049000, C700S050000, C714S724000, C714S725000, C714S728000
Reexamination Certificate
active
06181975
ABSTRACT:
The present invention is related generally to a method and system for carrying out surveillance of industrial processes using sensor or data source outputs. More particularly, the invention is concerned with a method and system for processing sensor data and using virtual data as an improved methodology over basic statistical approaches to industrial process surveillance. Further, the invention involves use of a plurality of techniques coupled for enhanced analysis of industrial process data.
Conventional parameter-surveillance schemes are sensitive only to gross changes in the mean value of a process or a 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, sensor deviation or data anomaly which gives rise to a signal below the threshold level for an alarm condition. Most methods also do not account for the relationship between a measurement by one sensor relative to another sensor measurement.
In another monitoring method, a conventional sequential probability ratio test (“SPRT”) technique has found wide application as a signal validation tool in the nuclear reactor industry. The SPRT method is a pattern recognition technique which processes the stochastic components associated with physical process variables and has high sensitivity for the onset of subtle disturbances in those variables. Two features of the conventional 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. SPRT techniques are primarily directed to the analysis of data from paired or multiple pairs of sensors in contrast to a large number of different process sensor data points. SPRT is also typically dependent on assumptions of the data being independent of other data sources and being Gaussian distributed data. The SPRT technique used alone therefore has certain shortcomings in identifying anomalies in processes.
Other types of statistical techniques also have been developed for industrial process monitoring and analysis but have other insensitivities for certain classes of sensor data.
It is, therefore, an object of the invention to provide an improved method and system for surveillance of industrial processes and apparati.
It is also an object of the invention to provide an improved method and system for evaluation of process data, on-line or off-line, from sensors or data accumulation sources.
It is a further object of the invention to provide a novel method and system for performing preliminary analysis of data for alarm conditions prior to data input to a SPRT system.
It is an additional object of the invention to provide an improved method and system for masking selected sensor data and substituting virtual data to perform tests to determine whether abnormal process conditions or abnormal sensor conditions exist and whether or not to halt or modify the process under scrutiny.
It is still another object of the invention to provide a novel method and system using training data characteristic of normal system and/or sensor and/or data source operation to compare with ongoing industrial processes and/or data accumulation.
It is yet a further object of the invention to provide an improved method and system for processing data from a process to determine training data for normal operation, storing such training data on a computer storage media and analyzing real process data relative to the normal training data using a plurality of mathematical methodologies stored on a ROM or PROM storage medium.
It is also an additional object of the invention to provide a novel method and system utilizing a virtual signal characteristic of normal state operation derived on the basis of correlation with a plurality of other process data values to compare with a real process data signal for deriving the likelihood of an abnormal process or operation of data sources.
It is yet another object of the invention to provide a novel method and apparatus to accumulate training data to recognize any one of a plurality of specific states of operation and thereby identify a particular type of fault or condition present in a process or other system.
It is also a further object of the invention to provide a novel method and apparatus for monitoring a process using training data to identify slowly changing operational sensor data characteristic of normal process changes.
It is still an object of the invention to provide an improved method and system for determining whether a system or data source abnormality can be ignored without undesirable effects.
Other advantages and features of the invention, together with the organization and manner of operation thereof, will become apparent from the following detailed description when taken in conjunction with the accompanying drawings described below.
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Gross Kenneth C.
Mott Jack E.
Singer Ralph M.
Wegerich Stephan W
ARCH Development Corporation
Foley & Lardner
Gordon Paul P.
Patel Ramesh
Rechtin Michael D.
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