Method for operating a technical facility

• US 20030004681A1
• Filed: 08/14/2002
• Published: 01/02/2003
• Est. Priority Date: 02/14/2000
• Status: Abandoned Application

• Current Assignee: Siemens AG
• Original Assignee: Siemens AG
• Inventors: Gassmann, Jorg, Gerlach, Andre, Fandrich, Jorg
• Application Number:
  US10/203,812
• Publication Number:
  US 20030004681A1
• Time in Patent Office: Days
• US Class Current: 702/183
• CPC Class Codes: G05B 13/0275 using fuzzy logic only
• CPC Class Codes: G05B 23/0229 knowledge based, e.g. expert systems; genetic algorithms
• CPC Class Codes: G05B 23/0289 Reconfiguration to prevent failure, e.g. usually as a reaction to incipient failure detection

Abstract

The invention concerns a method for operating a technical facility (2) comprising an expert system (1) for diagnosing (9) the operating state of the technical facility (2). Once the expert system (1) has identified a malfunction of the technical facility (2), the expert knowledge available in the knowledge base (WB) of the expert system (1) is also used parallel to the establishment of a diagnosis (9) to calculate a regulatory intervention (u) in the technical facility (2) with the purpose of automatically eliminating a malfunction.

Claims

1. A method for operating a technical facility with an expert system (1) for diagnosing (9) the operating state of the technical facility (2) characterized by the following steps:

a) in the expert system (1), a malfunction is identified, automatically triggering a regulating intervention in the technical facility;

b) at least one knowledge base (WB) available in the expert system is used—

in parallel with the diagnosis (9)—

to establish the regulating intervention (u);

c) the regulating intervention (u) in the technical facility is continued until the system deviation (e) lies in a specified tolerance band.

2. The method as claimed in claim 1, characterized in that the expert system (1) produces the diagnosis (9) by means of measured values (6) and the regulating intervention (u) is established at least from one of the measured values (6) and/or a variable derived from the measured values (6).

3. The method as claimed in claim 2, characterized in that the system deviation (e) and/or the change (de) in it is formed as variables derived from the measured values (6).

4. The method as claimed in one of claims 1 to 3, characterized in that the regulating intervention (u) is completely established by means of the knowledge base (WB).

5. The method as claimed in one of claims 1 to 4, characterized in that the knowledge base (WB) of the expert system (1) is formulated according to methods of fuzzy logic.

6. The method as claimed in claim 5, characterized in that the fuzzy logic contains specific, linguistic IF . . . THEN rules.

7. The method as claimed in claim 5 or 6, characterized in that the system deviation (e) and/or variables derived from it are fuzzified.

8. A hydrazine metering device for a water-steam cycle (22), characterized by

a first measuring element (14) for ascertaining a first measured value (6c) of the oxygen concentration in the feed water downstream of a condenser (26),

a second measuring element (12) for ascertaining a second measured value (6a) of the oxygen concentration in the feed water upstream of a steam generator (24),

a third measuring element (13) for ascertaining a third measured value (6b) of the concentration of hydrazine in the feed water upstream of the steam generator (24),

an expert system (31), which receives as input signals at least the measured values (6c, 6a, 6b) ascertained by the measuring elements (14, 12, 13), for producing a malfunction diagnosis with respect to an undesired entry of oxygen into the water-steam cycle (22) by means of symptoms (S) and rules (R) present in the knowledge base (29),

at least a first, a second and a third fuzzy controller (18c, 18a and 18b),

the first fuzzy controller (18c) being fed the first measured value (6c) and also a corresponding first setpoint value (32c),

the second fuzzy controller (18a) being fed the second measured value (6a) and also a corresponding second setpoint value (32a), and

the third fuzzy controller (18b) being fed the third measured value (6b) and also a corresponding third setpoint value (32b),

by means of the fuzzy controllers (18a, 18b, 18c), a regulating intervention (21a, 21b, 21c) with respect to a final controlling element (17) of a metering device (23) for hydrazine is calculated on the basis of a malfunction diagnosis produced by the expert system (31), by means of at least the first, the second and the third measured value (6c, 6a, 6b), using the symptoms (S) and rules (R) present in the knowledge base (29), and

a maximum-value selection element (33), by means of which the intervention of the greatest value is selected from the regulating interventions (21a, 21b, 21c) and switched to the final controlling element (17).