OIL DEBRIS MONITORING FOR FAILURE DETECTION ISOLATION

• US 20180023414A1
• Filed: 07/25/2016
• Published: 01/25/2018
• Est. Priority Date: 07/25/2016
• Status: Abandoned Application

• Current Assignee: Raytheon Technologies Corporation d/b/a RTX
• Original Assignee: United Technologies Corporation (Raytheon Technologies Corporation d/b/a RTX)
• Inventors: Hagen, Gregory S., Lin, Yiqing, Khibnik, Alexander I., Harris, Meggan, Erdinc, Ozgur, Giering, Michael J.
• Application Number:
  US15/218,307
• Publication Number:
  US 20180023414A1
• Time in Patent Office: Days
• CPC Class Codes: F01D 21/003 Arrangements for testing or measuring for measuring vibrations G01H
• CPC Class Codes: F02C 7/06 Arrangements of bearings bearings F16C; Lubricating of turbo machines F01D25/18; of machines or engines in general F01M
• CPC Class Codes: F05D 2220/32 in gas turbines
• CPC Class Codes: F05D 2260/98 Lubrication
• CPC Class Codes: F16N 2250/32 Inductive
• CPC Class Codes: F16N 29/04 enabling a warning to be given; enabling moving parts to be stopped
• CPC Class Codes: G01N 33/2858 metal particles
• CPC Class Codes: G01N 33/2888 Lubricating oil characteristics, e.g. deterioration lubricating properties G01N33/30

Abstract

A method of detecting debris within a lubricant stream, the method includes generating data indicative of debris and sensor system functionality within a lubricant stream with a sensor system. The data is communicated to a controller. Features calculated from the data are indicative of a debris within the lubricant stream. The calculated features are compiled over time during operation. The compiled features are classified. An oil debris monitoring system for a turbine engine is also disclosed.

Claims

1. A method of detecting debris within a lubricant stream, the method comprising:

generating data indicative of debris and sensor system functionality within a lubricant stream with a sensor system;

communicating the data to a controller;

calculating features from the data that are indicative of a debris within the lubricant stream;

compiling the calculated features over time during operation; and

classifying the compiled features.

2. The method as recited in claim 1, wherein classifying the compiled features includes determining an occurrence rate for the features.

3. The method as recited in claim 2, including comparing the determined occurrence rate with an expected range, and identifying an engine operational characteristic responsive to the comparison with the expected range.

4. The method as recited in claim 1, wherein the features comprise a plurality of features of the lubricant stream that are detected and identified concurrently.

5. The method as recited in claim 1, wherein the features comprise at least one of a time-rate of generation and an overall accumulated number of occurrences.

6. The method as recited in claim 5, wherein a time-rate of generation that corresponds with a desired operation of a turbine engine is compared to the determined time-rate of generation to identify an engine operational characteristic.

7. The method as recited in claim 1, wherein compiling the features is performed during operation of a turbine engine for analysis during a non-operating condition.

8. The method as recited in claim 7, including analysis of the compiled features for indications of debris within the lubricant stream indicative of a mechanical anomaly.

9. The method as recited in claim 7, including analysis of the compiled features for indications of an anomaly in operation of the sensor system.

10. An oil debris monitoring system for a turbine engine, the oil debris monitoring system comprising:

a sensor assembly mounted proximate to a lubricant conduit for generating a signal indicative of particles within a lubricant stream flowing through the lubricant conduit;

a feature generator configured to receive the signal from the sensor assembly and generate a data stream including features representing characteristics of the lubricant stream;

a feature accumulator configured to compile the features during an operational period of the turbine engine and storing the compiled features in a memory device; and

a fault isolator configured to classify the compiled features after the operational period is concluded and generate an output identifying anomalies in the features.

11. The system as recited in claim 10, wherein the fault isolator identifies anomalies indicative of a fault in the sensor assembly.

12. The system as recited in claim 10, wherein the fault isolator classifies the features according to an occurrence rate for the features.

13. The system as recited in claim 12, wherein the features comprise a plurality of features of the lubricant stream that are detected and identified concurrently.

14. The system as recited in claim 12, wherein the features comprise at least one of a time-rate of generation and an overall accumulated number of occurrences.

15. The system as recited in claim 10, wherein the feature generator and feature accumulator are part of a controller of the turbine engine.

16. The system as recited in claim 10, wherein classifying the compiled features includes determining an occurrence rate for the features.

17. The system as recited in claim 16, including comparing a determined occurrence rate with an expected range, and identifying an engine operational characteristic responsive to the comparison with the expected range.

18. The system as recited in claim 10, wherein the features comprise a plurality of features of the lubricant stream that are detected and identified concurrently.

19. The system as recited in claim 10, wherein the features comprise at least one of a time-rate of generation and an overall accumulated number of occurrences.

20. The system as recited in claim 19, wherein a time-rate of generation that corresponds with a desired operation of the turbine engine is compared to the determined time-rate of generation to identify an operational characteristic.