Apparatus and methods for detecting system faults using hidden process drivers
First Claim
1. A computer-based method for detecting faults in a system, the method comprising:
- grouping a plurality of sensors communicatively linked with the system into at least one group of correlated sensors based upon a measure of correlation between the plurality of sensors;
generating a hidden process driver for the at least one group of correlated sensors based upon a functional relationship between the hidden process driver and a set of sensor values produced by each of the correlated sensors;
estimating at least one parameter of the functional relationship based on a set of training data produced by the plurality of sensors, wherein estimating at least one parameter comprises estimating the at least one parameter based upon a least-squares regression on the set of training data;
generating a sensor estimate based upon the hidden process driver corresponding to the at least one group of correlated sensors and at least one known process driver;
detecting a fault when a residual based on a difference between a sensor value produced by a particular one of the plurality of sensors and a sensor estimate corresponding to that particular sensor lies outside a predetermined acceptable range of residuals for the particular sensor;
generating at least one response signal indicating the detected fault.
2 Assignments
0 Petitions
Accused Products
Abstract
An apparatus for detecting faults in a system monitored by a plurality of sensors is provided. The apparatus includes a hidden process driver unit that generates a hidden process driver based upon sensor values received from a group of correlated sensors selected from among the plurality of sensors. The apparatus also includes a sensor estimating unit that generates sensor estimates for each of the plurality of sensors based upon the hidden process driver and a known process driver provided by an uncorrelated sensor. The apparatus further includes a fault determining unit that indicates a fault when a residual based upon a difference between a sensor value supplied by one of the plurality of sensors and a corresponding one of the sensor estimates lies outside an acceptable range of residual values.
13 Citations
15 Claims
-
1. A computer-based method for detecting faults in a system, the method comprising:
-
grouping a plurality of sensors communicatively linked with the system into at least one group of correlated sensors based upon a measure of correlation between the plurality of sensors; generating a hidden process driver for the at least one group of correlated sensors based upon a functional relationship between the hidden process driver and a set of sensor values produced by each of the correlated sensors; estimating at least one parameter of the functional relationship based on a set of training data produced by the plurality of sensors, wherein estimating at least one parameter comprises estimating the at least one parameter based upon a least-squares regression on the set of training data; generating a sensor estimate based upon the hidden process driver corresponding to the at least one group of correlated sensors and at least one known process driver; detecting a fault when a residual based on a difference between a sensor value produced by a particular one of the plurality of sensors and a sensor estimate corresponding to that particular sensor lies outside a predetermined acceptable range of residuals for the particular sensor; generating at least one response signal indicating the detected fault. - View Dependent Claims (2, 3, 4, 5)
-
-
6. A computer-implemented method of estimating values of sensors used in monitoring a system, the method comprising:
-
grouping a plurality of sensors communicatively linked with the system into at least one group of correlated sensors based upon a measure of correlation between the plurality of sensors; generating a hidden process driver for the at least one group of correlated sensors based upon a plurality of inverse sensor functions and confidence weights, each of the plurality of inverse sensor functions and confidence weights uniquely corresponding to a different one of the group of correlated sensors; generating a sensor estimate based upon the hidden process driver corresponding to the at least one group of correlated sensors and at least one known process driver, wherein generating the sensor estimate comprises determining the sensor estimate upon a least-squares regression performed on a set of training data generated by the plurality of sensors; and generating at least one control signal indicating the sensor estimate. - View Dependent Claims (7, 8, 9)
-
-
10. An apparatus for detecting faults in a system monitored by a plurality of sensors, the apparatus comprising:
-
a hidden process driver unit that generates at least one hidden process driver based upon sensor values received from at least one group of correlated sensors selected from among the plurality of sensors, wherein the hidden process driver unit comprises a function determining module that determines a plurality of inverse sensor functions, each of the plurality of inverse sensor functions uniquely corresponding to a distinct one of the sensors belonging to the group of correlated sensors, and wherein the function determining module is configured to determine the at least one parameter based upon at least one least-squares statistic; a sensor estimating unit that generates at least one sensor estimate based upon the at least one hidden process driver and at least one known process driver provided by at least one uncorrelated sensor from among the plurality of sensors; and a fault determining unit that indicates a fault when a residual based upon a difference between a sensor value supplied by one of the plurality of sensors and a corresponding sensor estimate lies outside a predetermined acceptable range of residual values. - View Dependent Claims (11, 12, 13, 14, 15)
-
Specification