IP Library Granted Patent US 7,200,520
Granted Patent B2
US 7,200,520 · App. 10/528,732 · Granted Apr 3, 2007

Device and method for monitoring an electric power station

Assignee: Siemens Aktiengesellschaft
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Quick Facts
Patent No.
US 7,200,520
App. No.
10/528,732
Granted
Apr 3, 2007
Kind
B2
Abstract

The invention concerns a method and a corresponding device for monitoring a technical installation. The invention is characterized in that a dynamic model of at least one system of the technical installation is enhanced by means of an artificial intelligence based algorithm during the operation of said system.

Claims (23)

1. An electric power system comprising:

a power plant block; and

a device, including a computer system, coupled to receive data from the power plant block, the device including an analysis module for:

providing a dynamic model of a system of the power plant block, configured to generate output data based on the data received from the power plant block; and

implementing at least one algorithm based on artificial intelligence, that searches for dependencies or correlations among data received by the device, for integrating into the dynamic model new correlations based on said searches to improve the dynamic model of the system, thereby enabling provision of output data indicating changes in current or future operational behavior of the power plant block.

2. The system according to claim 1 , wherein an improvement of the dynamic model is based on continual acquisition of operational or structural data associated with a system in the power plant block, including data not previously used by the dynamic model, which data forms a basis to modify the dynamic model.

3. The system according to claim 1 , wherein the dynamic model further comprises an element from the group consisting of: a physical equation, a neural network, fuzzy logic, and a genetic algorithm.

4. The system according to claim 1 , wherein the dynamic model includes an neural network that is trained using historical operational data from the system.

5. The system according to claim 1 , wherein the device is configurable to include a plurality of analysis modules each including a dynamic model of a system of the power plant block and with said at least one algorithm based on artificial intelligence capable of providing correlations between the input and output data of a first of the analysis modules and the input and/or output data of a second of the analysis modules.

6. The system according to claim 5 , wherein the device is configurable to charactrerize future operational behavior of the power plant block based on cross-system information.

7. The system according to claim 1 , wherein the device is configured to process data from the group consisting of: process data, operational messages, warning messages, disruption messages, monitoring notifications, comments, design of the electric power station, hierarchy of the electric power station, and combinations thereof.

8. The system according to claim 1 , wherein the device is configured to process current and historical data associated with the plant power block.

9. The system according to claim 1 , wherein the plant power block comprises a process control system coupled to provide operational data and structural data, derived from multiple systems of the plant power block, to the device.

10. The system according to claim 1 , wherein the device is configurable with the algorithm based on artificial intelligence to develop relationships among individual correlations of the dynamic model and develop new parametric values based thereon.

11. A method for monitoring a system of the type including a power plant block, comprising:

acquiring system data during operation of the power plant block;

providing the data to a computer system;

using the data to exercise a first dynamic model of at least one system of the power plant block to provide output data indicative of plant operation;

modifying the dynamic model, with at least one algorithm based on artificial intelligence that searches for dependencies or correlations among acquired data, by integrating into the dynamic model new correlations based on said searches; and

providing the output data based on the modification of the dynamic model to characterize current or future operational behavior of the power plant block.

12. The method according to claim 11 , wherein the step of modifying the dynamic model includes acquiring input data which has not been previously used by the dynamic model.

13. The method according to claim 11 , wherein a plurality of additional dynamic models are exercised, each model describing operation of a system of the power plant block and wherein the step of modifying the first dynamic model includes developing correlations based on input data associated with the first dynamic model and input data associated with one of the additional dynamic models.

14. The method according to claim 13 , characterized in that the step of modifying the first dynamic model includes developing correlations between output data associated with the first dynamic model and said one of the additional dynamic models whereby the output data includes cross-system information.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 27, 2020
From: SIEMENS GAS AND POWER GMBH & CO. KG
To: SIEMENS AKTIENGESELLSCHAFT
Reel/Frame 054184/0990 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 28, 2020
From: SIEMENS AKTIENGESELLSCHAFT
To: SIEMENS GAS AND POWER GMBH & CO. KG
Reel/Frame 053624/0425 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 22, 2005
From: APPEL, MIRKO; FICK, WOLFGANG; GERK, UWE
To: SIEMENS AKTIENGESELLSCHAFT
Reel/Frame 016928/0001 →
Priority Claims (1)
EP 02021501 · Sep 26, 2002 · regional
Continuity (1)
Related Publication 20060025961A1 · Feb 2, 2006