Daniel F Chester

US Patent:

7451003, Nov 11, 2008

Filed:

Mar 4, 2004

Appl. No.:

10/793162

Inventors:

Daniel L. Chester - Newark DE, US
Stephen L. Daniel - Williamsville NY, US
Richard J. Fickelscherer - Forestville NY, US
Douglas H. Lenz - East Amherst NY, US

Assignee:

Falconeer Technologies LLC - Williamsville NY

International Classification:

G05B 13/02
G01F 1/00
G01F 7/00

US Classification:

700 28, 700 29, 700 50

Abstract:

The present invention provides an improved method and system for real-time monitoring, validation, optimization and predictive fault analysis in a process control system. The invention monitors process operations by continuously analyzing sensor measurements and providing predictive alarms using models of normal process operation and statistical parameters corresponding to normal process data, and generating secondary residual process models. The invention allows for the creation of a fault analyzer directly from linearly independent models of normal process operation, and provides for automatic generation from such process models of linearly dependent process models. Fuzzy logic is used in various fault situations to compute certainty factors to identify faults and/or validate underlying assumptions. In one aspect, the invention includes a real-time sensor data communications bridge module; a state transition logic module; a sensor validation and predictive fault analysis module; and a statistical process control module; wherein each of the modules operates simultaneously.

US Patent:

20090043405, Feb 12, 2009

Filed:

Oct 3, 2008

Appl. No.:

12/286912

Inventors:

Daniel L. Chester - Newark DE, US
Stephen L. Daniel - Williamsville NY, US
Richard J. Fickelscherer - Forestville NY, US
Douglas H. Lenz - East Amherst NY, US

International Classification:

G06N 7/02
G05B 9/02
G05B 13/02
G05B 13/04
G05B 19/00

US Classification:

700 28, 700 79, 700 51, 700 3, 700 50

Abstract:

The present invention provides an improved method and system for real-time monitoring, validation, optimization and predictive fault analysis in a process control system. The invention monitors process operations by continuously analyzing sensor measurements and providing predictive alarms using models of normal process operation and statistical parameters corresponding to normal process data, and generating secondary residual process models. The invention allows for the creation of a fault analyzer directly from linearly independent models of normal process operation, and provides for automatic generation from such process models of linearly dependent process models. Fuzzy logic is used in various fault situations to compute certainty factors to identify faults and/or validate underlying assumptions. In one aspect, the invention includes a real-time sensor data communications bridge module; a state transition logic module; a sensor validation and predictive fault analysis module; and a statistical process control module; wherein each of the modules operates simultaneously.