Method for blade temperature estimation in a steam turbine

• US 5,832,421 A
• Filed: 12/13/1996
• Issued: 11/03/1998
• Est. Priority Date: 12/13/1996
• Status: Expired due to Term

• Current Assignee: Siemens Corp. (Siemens AG)
• Original Assignee: Siemens Corporate Research Incorporated (Siemens AG)
• Inventors: Santoso, Nugroho Iwan, Petsche, Thomas
• Primary Examiner(s): Trammell, James P.
• Application Number:
  US08/764,381
• Time in Patent Office: 690 Days
• Field of Search: 364/557, 364/551.01, 364/550, 364/494, 364/495, 395/21, 395/22, 395/23, 395/902-904, 395/906, 395/907, 395/911, 395/912, 395/914, 395/915, 395/11, 395/24, 706/20, 706/21, 706/25, 702/130, 702/182, 702/60
• US Class Current: 702/130
• CPC Class Codes: F01K 13/02 Controlling, e.g. stopping or starting
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: Y10S 706/904 Manufacturing or machine, e.g. agricultural machinery, machine tool

Abstract

A method for blade temp estimation in a steam turbine utilizes measurement values including pressure and temperature at locations other than directly at the blades, principally at the input and output stages. Initially, blade temperature is simulated by using a water/steam cycle analysis program as well as by directed experiments. An artificial neural network (ANN) is trained by presenting the measurement values and the blade temp values. In a hybrid approach, 5 measured values are utilized. A subset of 4 parameter values is used for training the ANN and another subset of 3 values is used for performing a calculation for another intermediate parameter. Using the intermediate parameter and one of the 5 measured values, a blade temperature is calculated.

Claims

1. A method for blade temperature estimation in a steam turbine utilizes measurement parameter values including pressure and temperature at locations at least one of the input and output stages, comprising the steps of:

simulating blade temperature values by using a water/steam cycle analysis program and by directed experiments;

training an artificial neural network (ANN) by presenting it with said measurement values and said blade temperature values; and

applying real time measurement values to said ANN.

2. A method for blade temperature estimation in accordance with claim 1, wherein said measurement values are four in number.

3. A method for blade temperature estimation in accordance with claim 1 wherein said ANN is used directly to derive operating blade temperature values.

4. A method for blade temperature estimation in accordance with claim including the steps of:

creating a first subset of said parameter values;

utilizing said first subset for training said ANN;

creating a second subset of said parameter values;

utilizing said second subset for performing a calculation for deriving an intermediate parameter; and

utilizing said intermediate parameter and one of said measured parameter values to calculate a blade temperature value.

5. A method for blade temperature estimation in accordance with claim 4, wherein 5 measured parameter values are utilized and said first ubset comprises 4 measured parameters.