METHOD AND SYSTEM FOR FAILURE PREDICTION USING LUBRICATING FLUID ANALYSIS

• US 20140121994A1
• Filed: 10/26/2012
• Published: 05/01/2014
• Est. Priority Date: 10/26/2012
• Status: Active Grant

• Current Assignee: Pratt & Whitney Canada Corporation (Raytheon Technologies Corporation d/b/a RTX)
• Original Assignee: Pratt & Whitney Canada Corporation (Raytheon Technologies Corporation d/b/a RTX)
• Inventors: JEAN, Maurice, MEILLEUR, Daniel
• Granted Patent: US 9,897,582 B2
• Time in Patent Office: Days
• US Class Current: 702/27
• CPC Class Codes: F01M 2011/14 for indicating the necessity to change the oil
• CPC Class Codes: F02D 41/22 Safety or indicating devices for abnormal conditions in air/fuel ratio feedback systems F02D41/1495, in electric control linkage F02D11/107, in purge control systems F02M25/0809
• CPC Class Codes: G01N 31/22 using chemical indicators G01N31/02 takes precedence
• CPC Class Codes: G01N 33/2858 metal particles
• CPC Class Codes: G06F 15/00 Digital computers in general details G06F1/00 – G06F13/00; Data processing equipment in general
• CPC Class Codes: Y02T 10/40 Engine management systems

Abstract

Methods and systems for failure prediction using analysis of oil or other lubricant. Raw data about feature(s) of each of a plurality of particles filtered from a fluid sample are used to categorize each particle into one of a plurality of categories, each category being defined by one or more of: chemical composition, size and morphology. Particle physical characteristics in each category are quantified to obtain a set of categorized data. The categorized data are compared with historical data. Results of the comparing are evaluated to generate a prediction of any failure or mechanism of failure.

Claims

1. A method for failure prediction in an engine, the method being implemented by a processor, the method comprising:

receiving raw data representing a plurality of features of each of a plurality of particles filtered from a fluid sample obtained from the engine, the engine belonging to an engine type;

wherein the plurality of features includes at least one physical characteristic and chemical composition;

categorizing each particle into one of a plurality of categories according to at least one of the plurality of features by calculating a likelihood that a given particle belongs to a given category, each category being defined by one or more of;

chemical composition, size and morphology;

quantifying particle physical characteristics in each category to obtain a set of categorized data;

comparing the set of categorized data with at least one set of historical data associated with the engine type, the historical data being retrieved from a database;

evaluating results of the comparing using a set of predefined rules to generate a prediction of any failure or mechanism of failure; and

generating an output indicating the prediction.

2. The method of claim 1, wherein quantifying comprises determining a number of particles for a given category, and normalizing the number of particles.

3. The method of claim 1, wherein each particle within each category is further sorted into a plurality of bins according to physical characteristics, wherein quantifying the particle physical characteristics in each category comprises determining a number of particles sorted into each bin.

4. The method of claim 1, wherein the physical characteristics comprise at least one of a size and a morphology of each particle.

5. The method of claim 1, wherein the chemical composition comprises at least one of an elemental composition and an alloy composition of each particle.

6. The method of claim 1, wherein the at least one set of historical data is in the form of a historical model generated from a plurality of sets of historical data.

7. The method of claim 1, wherein the plurality of particles comprise particles smaller than about 30 μ

m in diameter.

8. The method of claim 1, wherein the plurality of particles comprises particles sized in the range of about 0.5 μ

m to about 1600 μ

m in diameter.

9. The method of claim 1, wherein the plurality of categories comprise at least one sub-category.

10. The method of claim 1, wherein the plurality of categories comprises at least one category defined according to:

elemental composition, alloy composition and particle source.

11. The method of claim 1, wherein the comparison comprises at least one of a calculation of deviation of the categorized data from the historical data, and a calculation of variation of the categorized data from the historical data.

12. The method of claim 1, wherein the comparison comprises at least one of a comparison of the categorized data in each category to the historical data, and a comparison of a composite of the categorized data to the historical data.

13. The method of claim 1, wherein the predicted mechanism of failure comprises at least one of a determination of premature wear of an engine component and a determination of an expected failure of an engine.

14. The method of claim 13 wherein the predicted mechanism of failure includes at least one of:

excess vibration, bearing wear, external contamination following engine maintenance, bearing rubbing, gear degradation, and bearing cage and race degradation.

15. The method of claim 1, wherein the engine is an aircraft engine.

16. The method of claim 1, wherein the fluid is oil or other lubricant from the engine.

17. The method of claim 1, wherein the determining comprises performing particle analysis using X-ray spectroscopy.

18. A system for fluid analysis, the system comprising a processor and a memory containing machine-readable instructions for execution by the processor, the machine-readable instructions causing the processor to carry out the method of claim 1.

19. The system of claim 18 further comprising spectroscopy equipment for carrying out particle analysis for the determining.

20. A non-transitory computer-readable medium or media embodying computer-executable instructions configured for causing one or more processors to carry out the method of claim 1.