Analysis of time-series data from an electric power-producing asset for the inference of well-defined overlapping modes (ModeMonitor)

• US 20050209799A1
• Filed: 01/27/2005
• Published: 09/22/2005
• Est. Priority Date: 01/29/2004
• Status: Abandoned Application

• Current Assignee: Andrew G. Poush, Bradley M. Lewis, Patryk A. Laurent
• Original Assignee: Andrew G. Poush, Bradley M. Lewis, Patryk A. Laurent
• Inventors: Laurent, Patryk A., Poush, Andrew G., Lewis, Bradley M.
• Application Number:
  US11/045,622
• Publication Number:
  US 20050209799A1
• Time in Patent Office: Days
• US Class Current: 702/62
• CPC Class Codes: G05B 23/0264 Control of logging system, e.g. decision on which data to store; time-stamping measurements

Abstract

This invention relates to a maximization of the inferences which are derived from data involved in data processing representing asset modes based on applicable state representations. The maximization takes place using a single algorithm to automatically analyze information and infer from electric power turbine configurations.

Claims

1. What is claimed is an algorithm for the analysis of time-series data from an electric power producing asset (such as a combustion chamber) in order to infer a set of well-defined modes (see Glossary) for the asset, based on event driven data (such as controller events and alarms) and periodic data (such as controller data point values polled every 30 sec.) available from the asset.

2. The system of method in [1] and a network carrying various combinations of communications protocols, such as TCP/IP, ODBC, OPC, GSM (GE Standard Messaging).

3. The system combining such a method as in [1 ] with a web-based management and information capture system which reflects up-to-date measurements and status information on turbines.

4. The system combining method [1] and a database system capable of storing data obtained through various communications protocols, which can be used to quantify data from a turbine after the operation has occurred. The modes allow periodic data to be stored selectively (that is only when it is of interest or relevant) and results in enhanced performance of the database.

5. The use of various combinations of methods and systems in [1]. [2]. [3] and [4] with many types of electric power generation including combustion turbines, aeroderivative turbines, steam turbines, hydroelectric, geothermal, wind, solar, nuclear and similar power-generating devices which produce digital and analog data related to their production of power. The modes provide a systematic basis for facilitating the automated calculation of asset performance parameters (such as fuel consumption, power production, and wear estimation of parts.)

6. A system which collects information from the systems claimed in [3], [4] and [5] from one or more turbine-holding clients with the purpose of generated comparative performance reporting among clients, where such clients may remain anonymous.