SYSTEM AND METHOD FOR ADVANCED CONDITION MONITORING OF AN ASSET SYSTEM
First Claim
1. A method for advanced condition monitoring of an asset system, the method comprising the steps of:
- segmenting an operating space of an asset system into a plurality of operating regimes;
using a plurality of auto-associative neural networks (AANNs) to determine estimates of actual values sensed by the at least one sensor in at least one of the plurality of operating regimes;
determining a residual between the estimated sensed values and the actual values sensed by the at least one sensor from each of the plurality of auto-associative neural networks;
combining the residuals by using a fuzzy supervisory model blender;
performing a fault diagnostic on the combined residuals;
determining a change of the operation of the asset system by analysis of the combined residuals; and
providing an alert if a change of the operation of the asset system has been determined.
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Abstract
A method for advanced condition monitoring of an asset system includes using a plurality of auto-associative neural networks to determine estimates of actual values sensed by at least one sensor in at least one of the plurality of operating regimes; determining a residual between the estimated sensed values and the actual values sensed by the at least one sensor from each of the plurality of auto-associative neural networks; and combining the residuals by using a fuzzy supervisory model blender; performing a fault diagnostic on the combined residuals; and determining a change of the operation of the asset system by analysis of the combined residuals. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.
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Citations
15 Claims
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1. A method for advanced condition monitoring of an asset system, the method comprising the steps of:
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segmenting an operating space of an asset system into a plurality of operating regimes; using a plurality of auto-associative neural networks (AANNs) to determine estimates of actual values sensed by the at least one sensor in at least one of the plurality of operating regimes; determining a residual between the estimated sensed values and the actual values sensed by the at least one sensor from each of the plurality of auto-associative neural networks; combining the residuals by using a fuzzy supervisory model blender; performing a fault diagnostic on the combined residuals; determining a change of the operation of the asset system by analysis of the combined residuals; and providing an alert if a change of the operation of the asset system has been determined. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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Specification