Method and apparatus for detecting multiple anomalies in a cluster of components
First Claim
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1. A method for detecting multiple anomalies in a cluster of components, comprising:
- monitoring one or more inferential variables that are received from sensors in the cluster of components;
obtaining derivatives from the one or more inferential variables using a moving-window numerical derivative technique to calculate the rate-of-change in the one or more inferential variables over a specified time interval;
monitoring the derivatives obtained from the one or more inferential variables;
determining whether one or more components within the cluster have experienced an anomalous event based on the monitored derivatives; and
if so, performing one or more remedial actions.
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Abstract
A system that detects multiple anomalies in a cluster of components is presented. During operation, the system monitors derivatives obtained from one or more inferential variables which are received from sensors in the cluster of components. The system then determines whether one or more components within the cluster have experienced an anomalous event based on the monitored derivatives. If so, the system performs one or more remedial actions.
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Citations
23 Claims
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1. A method for detecting multiple anomalies in a cluster of components, comprising:
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monitoring one or more inferential variables that are received from sensors in the cluster of components; obtaining derivatives from the one or more inferential variables using a moving-window numerical derivative technique to calculate the rate-of-change in the one or more inferential variables over a specified time interval; monitoring the derivatives obtained from the one or more inferential variables; determining whether one or more components within the cluster have experienced an anomalous event based on the monitored derivatives; and if so, performing one or more remedial actions. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for detecting multiple anomalies in a cluster of components, wherein the method comprises:
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monitoring one or more inferential variables that are received from sensors in the cluster of components; obtaining derivatives from the one or more inferential variables using a moving-window numerical derivative technique to calculate the rate-of-change in the one or more inferential variables over a specified time interval; monitoring the derivatives obtained from the one or more inferential variables; determining whether one or more components within the cluster have experienced an anomalous event based on the monitored derivatives; and if so, performing one or more remedial actions. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. An apparatus that detects multiple anomalies in a cluster of components, comprising:
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a monitoring mechanism configured to; monitor one or more inferential variables that are received from sensors in the cluster of components; obtain derivatives from the one or more inferential variables using a moving-window numerical derivative technique to calculate the rate-of-change in the one or more inferential variables over a specified time interval; and monitor the derivatives obtained from the one or more inferential variables; an analysis mechanism configured to determine whether one or more components within the cluster have experienced an anomalous event based on the monitored derivatives; and a remedial action mechanism, wherein if the analysis mechanism determines that one or more components within the cluster has failed, the remedial action mechanism is configured to perform one or more remedial actions.
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16. A method for detecting multiple anomalies in a cluster of components, comprising:
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monitoring derivatives obtained from one or more inferential variables which are received from sensors in the cluster of components; determining whether one or more specified events occurred within the cluster of components based on the monitored derivatives; and if so, determining the probability that the cluster of components is in a specified state based on the one or more specified events that occurred by determining the number of first events x and second events y that occurred; and determining the probability pi,j that the cluster of components is in a specified state |i,j>
as; - View Dependent Claims (17, 18, 19)
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20. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for detecting multiple anomalies in a cluster of components, wherein the method comprises:
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monitoring derivatives obtained from one or more inferential variables which are received from sensors in the cluster of components; determining whether one or more specified events occurred within the cluster of components based on the monitored derivatives; and if so, determining the probability that the cluster of components is in a specified state based on the one or more specified events that occurred by determining the number of first events x and second events y that occurred; and determining the probability pi,j that the cluster of components is in a specified state |i,j>
as; - View Dependent Claims (21, 22, 23)
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Specification