Evaluating anomaly for one class classifiers in machine condition monitoring
First Claim
Patent Images
1. A method for evaluating an anomaly measurement x′
- in a machine condition monitoring system including a processor, wherein measurements xi are evaluated in a one-class classifier having a decision region R1 for the class C1 such that an evaluation function ƒ
(x) is greater than or equal to a threshold T for a measurement x within the region, and less than T outside the region the method comprising the steps of;
training the one-class classifier to establish the decision region R1 from a set of training samples {x1, x2, . . . , xN};
receiving the anomaly measurement x′
;
determining that the anomaly measurement is outside the region R1;
determining, using the processor, a distance from the measurement x′
to a boundary of the region R1; and
evaluating the anomaly measurement x′
based on the distance;
wherein the step of determining a distance from the measurement x′
to the region R1 further comprises the steps of;
finding a closest sample q, in the region R1, to the measurement x′
;
defining an average point m between the x′ and
q;
if a difference between ƒ
(m) and T is greater than a permissible error, then if ƒ
(m)<
T, assign m to x′ and
return to the defining step; and
if ƒ
(m)>
T, assign m to q and return to the defining step; and
if the difference is less than the permissible error, assigning a distance from the measurement x′
to m as the distance from the measurement x′
to a boundary of the region R1.
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Abstract
A method for monitoring machine conditions provides additional information using a one-class classifier in which an evaluation function is learned. In the method, a distance is determined from an anomaly measurement x to a boundary of a region R1 containing all acceptable measurements. The distance is used as a measure of the extent of the anomaly. The distance is found by searching along a line from the anomaly to a closest acceptable measurement within the region R1.
9 Citations
16 Claims
-
1. A method for evaluating an anomaly measurement x′
- in a machine condition monitoring system including a processor, wherein measurements xi are evaluated in a one-class classifier having a decision region R1 for the class C1 such that an evaluation function ƒ
(x) is greater than or equal to a threshold T for a measurement x within the region, and less than T outside the region the method comprising the steps of;training the one-class classifier to establish the decision region R1 from a set of training samples {x1, x2, . . . , xN}; receiving the anomaly measurement x′
;determining that the anomaly measurement is outside the region R1; determining, using the processor, a distance from the measurement x′
to a boundary of the region R1; andevaluating the anomaly measurement x′
based on the distance;wherein the step of determining a distance from the measurement x′
to the region R1 further comprises the steps of;finding a closest sample q, in the region R1, to the measurement x′
;defining an average point m between the x′ and
q;if a difference between ƒ
(m) and T is greater than a permissible error, then if ƒ
(m)<
T, assign m to x′ and
return to the defining step; and
if ƒ
(m)>
T, assign m to q and return to the defining step; andif the difference is less than the permissible error, assigning a distance from the measurement x′
to m as the distance from the measurement x′
to a boundary of the region R1. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
- in a machine condition monitoring system including a processor, wherein measurements xi are evaluated in a one-class classifier having a decision region R1 for the class C1 such that an evaluation function ƒ
-
9. A computer-usable medium having computer readable instructions stored thereon for execution by a processor to perform a method evaluating an anomaly measurement x′
- in a machine condition monitoring system wherein measurements xi are evaluated in a one-class classifier having a decision region R1 for the class C1 such that an evaluation function ƒ
(x) is greater than or equal to a threshold T for a measurement x within the region, and less than T outside the region, the method comprising the steps of;training the one-class classifier to establish the decision region R1 from a set of training samples {x1, x2, . . . , xN}; receiving the anomaly measurement x′
;determining that the anomaly measurement is outside the region R1; determining a distance from the measurement x′
to a boundary of the region R1; andevaluating the anomaly measurement x′
based on the distance;wherein the step of determining a distance from the measurement x′
to the region R1 further comprises the steps of;finding a closest sample q, in the region R1, to the measurement x′
;defining an average point m between the x′ and
q;if a difference between ƒ
(m) and T is greater than a permissible error, then if ƒ
(m)<
T, assign m to x′ and
return to the defining step; and
if ƒ
(m)>
T, assign m to q and return to the defining step; andif the difference is less than the permissible error, assigning a distance from the measurement x′
to m as the distance from the measurement x′
to a boundary of the region R1. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
- in a machine condition monitoring system wherein measurements xi are evaluated in a one-class classifier having a decision region R1 for the class C1 such that an evaluation function ƒ
Specification