System, device, and methods for updating system-monitoring models

• US 20060047512A1
• Filed: 08/24/2005
• Published: 03/02/2006
• Est. Priority Date: 08/27/2004
• Status: Active Grant

• Current Assignee: Siemens Energy Incorporated (Siemens AG)
• Original Assignee: Siemens Energy Incorporated (Siemens AG)
• Inventors: Fang, Ming, Neubauer, Claus, Yuan, Chao, Cataltepe, Zehra, Brummel, Hans-Gerd, McCorkle, Wesley
• Granted Patent: US 7,457,674 B2
• Time in Patent Office: Days
• US Class Current: 704/244
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05B 23/0243 model based detection method, e.g. first-principles knowledge model

Abstract

A system for updating a plurality of monitoring models is provided. The system includes a model association module that, for each of a plurality of monitored systems determines, an association between a particular monitored system and at least one of a plurality of estimation models. Each estimation model is based upon one of a plurality of distinct sets of estimation properties, and each set uniquely corresponds to a particular estimation model. The system also includes an updating module that updates at least one of the estimation properties and propagates the updated estimation properties to each estimation model that corresponds to a distinct set containing at least one estimation property that is updated. The system further includes a model modification module that modifies each estimation model that corresponds to a distinct set containing at least one estimation property that is updated.

Claims

1. An electronically-implemented model association method for updating estimation models used for system monitoring, the method comprising:

for each of a plurality of monitored systems, determining an association between a particular monitored system and at least one of a plurality of estimation models, wherein each estimation model is based upon one of a plurality of distinct sets of estimation properties and wherein each set uniquely corresponds to a particular estimation model;

updating at least one of the estimation properties;

propagating the at least one updated estimation property to each estimation model that corresponds to a distinct set containing the at least one estimation property that is updated; and

modifying each estimation model that corresponds to a distinct set containing the at least one estimation property that is updated.

2. The method of claim 1, further comprising updating at least one association between a monitored system and an associated estimation model.

3. The method of claim 1, further comprising training a system-specific version of each estimation model for each monitored system, wherein the training is based upon sensor data generated by sensors communicatively linked to a particular system for which a particular system-specific version of an estimation model is trained.

4. The method of claim 1, further comprising retraining each system-specific version of each estimation model that is modified, wherein the retraining is based upon sensor data generated by sensors communicatively linked to a particular system for which a particular system-specific version of an estimation model is retrained.

5. The method of claim 4, wherein retraining is based upon a least-squares estimation.

6. The method of claim 1, wherein the estimation properties comprise at least one of a sensor list, a sensor threshold, a training period, an algorithm, and at least one algorithm parameter.

7. The method of claim 1, further comprising generating a fleet table to represent the associations between the plurality of monitored systems and the plurality of estimation models.

8. The method of claim 7, wherein the fleet table comprises an M×

N matrix, M being an integer greater than one comprising a number of monitored systems, and N being an integer equal to a number of estimation models.

9. A system for updating a plurality of monitoring models, the system comprising:

a model association module that for each of a plurality of monitored systems determines an association between a particular monitored system and at least one of a plurality of estimation models, wherein each estimation model is based upon one of a plurality of distinct sets of estimation properties and wherein each set uniquely corresponds to a particular estimation model;

an updating module that updates at least one of the estimation properties and propagates the at least one updated estimation property to each estimation model that corresponds to a distinct set containing the at least one estimation property that is updated; and

a model modification module that modifies each estimation model that corresponds to a distinct set containing the at least one estimation property that is updated.

10. The system of claim 9, wherein the model association module is configured to update associations between the monitored systems and the associated estimation models.

11. The system of claim 10, further comprising a training module configured to train a system-specific version of each estimation model for each monitored system based upon sensor data generated by sensors communicatively linked to a particular system for which a particular system-specific version of an estimation model is trained.

12. The system of claim 11, wherein the training module is further configured to retrain each system-specific version of each estimation model that is modified.

13. The system of claim 9, wherein the estimation properties comprise at least one of a sensor list, a sensor threshold, a training period, an algorithm, and an algorithm parameter.

14. The system of claim 9, wherein the system is deployed at a location remote from the plurality of monitored systems.

15. A computer-readable storage medium comprising computer instructions for:

determining for each of a plurality of monitored systems an association between a particular monitored system and at least one of a plurality of estimation models, wherein each estimation model is based upon one of a plurality of distinct sets of estimation properties and wherein each set uniquely corresponds to a particular estimation model;

updating at least one of the estimation properties;

propagating at least one updated estimation property to each estimation model that corresponds to a distinct set containing the at least one estimation property that is updated; and

modifying each estimation model that corresponds to a distinct set containing the at least one estimation property that is updated.

16. The computer-readable storage medium of claim 15, further comprising computer instructions for updating at least one association between a monitored system and an associated estimation model.

17. The computer-readable storage medium of claim 15, further comprising computer instructions for training a system-specific version of each estimation model for each monitored system, wherein the training is based upon sensor data generated by sensors communicatively linked to a particular system for which a particular system-specific version of an estimation model is trained.

18. The computer-readable storage medium of claim 15, further comprising computer instructions for retraining each system-specific version of each estimation model that is modified, wherein the retraining is based upon sensor data generated by sensors communicatively linked to a particular system for which a particular system-specific version of an estimation model is retrained.

19. The computer-readable storage medium of claim 18, wherein the computer instructions for retraining comprise instructions for performing estimations based upon a least-squares method.

20. The computer-readable storage medium of claim 15, wherein the estimation properties comprise at least one of a sensor list, a sensor threshold, a training period, an algorithm, and at least one algorithm parameter.