System and method for processing a new diagnostics case relative to historical case data and determining a ranking for possible repairs

• US 7,206,965 B2
• Filed: 05/23/2003
• Issued: 04/17/2007
• Est. Priority Date: 05/23/2003
• Status: Expired due to Fees

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Varma, Anil, Roddy, Nicholas Edward
• Primary Examiner(s): Beausoliel; Robert
• Assistant Examiner(s): Riad; Amine
• Application Number:
  US10/444,528
• Publication Number:
  US 20040250163A1
• Time in Patent Office: 1,425 Days
• Field of Search: 714/25, 714/47, 707/6, 707/3, 707/4
• US Class Current: 714/25
• CPC Class Codes: G06F 11/2257 using expert systems

Abstract

Method and system are provided for processing a new diagnostics case relative to historical case data for a machine undergoing diagnostics. The method allows providing a database storing historical case data for the machine undergoing diagnostics. The method further allows calculating a degree of similarity between the new case and respective cases stored in the database. A list of neighboring cases is determined relative to the new case based on the calculated degree of similarity between the new case and the respective cases stored in the database. The list of neighboring cases is processed to determine a ranking for possible corrective actions for the new case. A corrective action is selected for the new case based on the ranking of the possible corrective actions for the new case.

Claims

1. A method for processing a new diagnostics case relative to historical case data for a machine undergoing diagnostics, the method comprising:

providing a database storing historical case data for the machine undergoing diagnostics;

calculating a degree of similarity between the new case and respective cases stored in the database;

determining a list of neighboring cases relative to the new case based on the calclated degree of similarity between the new case and the respective cases stored in the database;

processing the list of neighboring cases to determine a ranking for possible corrective actions for the new case; and

selecting a corrective action for the new case based on the ranking of the possible corrective actions for the new case, wherein the calculated degree of similarity (S) is based on the following equation,

2. The method of claim 1 wherein the ranking for possible corrective actions for the new case is based, at least in part, on a rank difference between respective ones of the possible corrective actions.

3. The method of claim 1 wherein the ranking of the possible corrective actions is a relative ranking among the possible corrective actions.

4. A method for processing a new diagnostics case relative to historical case data for a machine undergoing diagnostics, the method comprising:

providing a database storing historical case data for the machine undergoing diagnostics;

calculating a degree of similarity between the new case and respective cases stored in the database;

determining a list of neighboring cases relative to the new case based on the calculated degree of similarity between the new case and the respective cases stored in the database;

processing the list of neighboring cases to determine a ranking for possible corrective actions for the new case; and

selecting a corrective action for the new case based on the ranking of the possible corrective actions for the new case, wherein the ranking for possible corrective actions for the new case is based one the following equation

for (i=1;

i<

n;

i=i+1) and

for (j=i+1;

j<

=n;

j=j+1),

{if((Rci=Rcj)}, then {Mi=Mi+1/(j−

i+β

)*Mj}

wherein Rci represents a corrective action for a case at rank i, Rcj represents a corrective action for a case at rank j,

Mi represents a match percentage for the case at rank i,

Mj represents a match percentage for the case at rank j,

N represents a total number of neighboring cases, and

β

represents a predefined damping factor.

5. The method of claim 4 wherein the degree of similarity is a numerical determination.

6. The method of claim 4 wherein the degree of similarity is based, at least in part, on a frequency of occurrence of faults shared in common between the new case and the respective cases stored in the database.

7. A system for processing a new diagnostics case relative to historical case data for a machine undergoing diagnostics, the system comprising:

a database storing historical case data for the machine undergoing diagnostic;

a processor configured to calculate a degree of similarity between the new case and respective cases stored in the database;

a processor configured to determine a list of neighboring cases relative to the new case based on the calculated degree of similarity between the new case and the respective cases stored in the database, wherein the calculated degree of similarity (S) is based on the following equation,

8. The system of claim 7 further comprising a processor configured to calculate a relative ranking among the possible corrective actions.

9. The system of claim 7 wherein said processors are modules of a single processor device.

10. A system for processing a new diagnostics case relative to historical case data for a machine undergoing diagnostics, the system comprising:

a database storing historical case data for the machine undergoing diagnostics;

a processor configured to calculate a degree of similarity between the new case and respective cases stored in the database;

a processor configured to determine a list of neighboring cases relative to the new case based on the calculated degree of similarity between the new case and the respective cases stored in the database; and

a processor configured to process the list of neighboring cases to determine a ranking for possible corrective actions for the new case, wherein the system selects a corrective action for the new case based on the ranking of the possible corrective actions for the new case, wherein the ranking for possible corrective actions for the new case is based one the following equation

for (i=1;

i<

n;

i=i+1) and

for (j=i+1;

j<

=n;

j=j+1),

{if((Rci=Rcj)}, then {Mi=Mi+1/(j−

i+β

)*Mj},

wherein Rci represents a corrective action for a case at rank i, Rcj represents a corrective action for a case at rank j,

Mi represents a match percentage for the case at rank i,

Mj represents a match percentage for the case at rank j,

N represents a total number of neighboring cases, and

β

represents a predefined damping factor.

11. The system of claim 10 further comprising a processor configured to calculate a numerical degree of similarity.