System and method for prediction of gas turbine trips due to thermocouple failures

• US 7,734,443 B2
• Filed: 08/23/2007
• Issued: 06/08/2010
• Est. Priority Date: 08/23/2007
• Status: Active Grant

• Current Assignee: GE Infrastructure Technology, LLC (GE Vernova, Inc.)
• Original Assignee: General Electric Company
• Inventors: De, Soumen, Pandey, Achalesh Kumar, Babu, Ravi Yoganatha, Jammu, Viany Bhaskar, Rucigay, Richard John
• Primary Examiner(s): Hellner; Mark
• Application Number:
  US11/843,939
• Publication Number:
  US 20090055070A1
• Time in Patent Office: 1,020 Days
• Field of Search: 701/132, 701/130, 701/131, 700/287, 236/15.BB, 60/390.91, 702/130, 702/132, 702/131
• US Class Current: 702/132
• CPC Class Codes: F02C 9/00 Controlling gas-turbine plants; Controlling fuel supply in air- breathing jet-propulsion plants controlling air intakes F02C7/057; controlling turbines F01D; controlling compressors F04D27/00; controlling in general G05
• CPC Class Codes: F05D 2260/80 Diagnostics
• CPC Class Codes: G05B 23/0283 Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06

Abstract

Systems and methods for prediction of gas turbine trips due to component failures such as thermocouple failures. Exemplary embodiments include prediction of gas turbine trips due to component failures, including collecting raw gas turbine operational data and using the raw gas turbine operational data to generate a prognostic indicator for the prediction of a turbine trip due to the failed thermocouples.

Claims

1. A system for the prediction of gas turbine trips due to thermocouple failures, the system comprising:

a turbine;

a local computer coupled to the turbine for collecting raw turbine operational data indicative of any thermocouple failures from the turbine;

a process, residing on the local computer, for computing a prediction of turbine trips by extractincg features indicative of any thermocouple failure from the raw turbine operational data, the process including instructions to generate a prognostic indicator for the prediction of any turbine trip;

a remote computer coupled to the local computer configured to;

perform a trip reduction analysis by applying a rule set to the extracted features;

generate recommendations to prevent the turbine trips based upon the trip reduction analysis; and

a database coupled to the remote computer for storing information related to any trips of the turbine.

2. The system as claimed in claim 1, wherein the database comprises a computer readable medium having a plurality of data nodes stored on the medium and representing a data structure, comprising:

a first data node stored in a first region of a range of memory addresses in the medium, the first data node representing a time to trip indicator;

a second data node stored in a second region of a range of memory addresses in the medium, the second data node representing trip mitigation recommendations; and

an index stored in an index region of the range of memory addresses, the index storing relationship information between the first and second data nodes, wherein the second process includes instructions to generate appropriate action to mitigate the trip.

3. The system as claimed in claim 2, wherein the appropriate action to mitigate the trip is at least one of a graceful shutdown of the turbine and a repair of the failed thermocouple.

4. The method as claimed in claim 1, wherein thermocouple features indicative of a turbine trip include at least one of a maximum standard deviation based on thermocouple fluctuations, a cumulative value of combustion in excess of a maximum threshold, a cumulative value of a thermocouple trouble alarm, and a cumulative value of a spread2 exceedance.