Bearing anomaly detection and location

• US 20050119840A1
• Filed: 12/15/2003
• Published: 06/02/2005
• Est. Priority Date: 01/10/2003
• Status: Active Grant

• Current Assignee: Rolls-Royce PLC (Rolls-Royce Holdings Plc)
• Original Assignee: Rolls-Royce PLC (Rolls-Royce Holdings Plc)
• Inventors: Anuzis, Paul, King, Stephen Peter, Astley, Kenneth Richard, King, Dennis Maxwell
• Granted Patent: US 6,999,884 B2
• Time in Patent Office: Days
• US Class Current: 702/56
• CPC Class Codes: G01M 13/045 Acoustic or vibration analysis
• CPC Class Codes: G01N 2291/2696 Wheels, Gears, Bearings

Abstract

A method for monitoring the health of a system comprises performing at each of a plurality of times the steps of: constructing a condition signature (30) from a plurality of condition indicators including (a) a plurality of vibration measurements acquired from the system or (b) one or more vibration measurements and one or more performance parameter measurements acquired from the system; predicting a normal signature (32) from a model defining one or more inter-dependencies between said condition indicators, the normal signature corresponding to the condition signature for a healthy system; comparing the condition signature with the normal signature; and registering an event if the condition signature differs from the normal signature by more than a predetermined threshold.

Claims

1. A method for locating bearing anomalies in machinery, which comprises:

receiving vibration measurements acquired from the machinery,

analysing the vibration measurements to identify novel tracked orders indicative of bearing anomalies, and

ascertaining the location of a bearing anomaly by relating a novel tracked order thus-identified to one or more further tracked orders.

2. A method according to claim 1, wherein the further tracked orders comprise at least one side-band to the novel tracked order.

3. A method according to claim 1, wherein the further tracked orders comprise a tracked order associated with a component supported by the anomalous bearing.

12. A method according to claim 1, wherein the machinery comprises a gas turbine engine.

4. A method for detecting bearing anomalies in machinery, which comprises performing at each of a plurality of times the steps of:

constructing a condition signature from a plurality of condition indicators including (a) a plurality of vibration measurements acquired from the machinery or (b) one or more vibration measurements and one or more performance parameter measurements acquired from the machinery;

predicting a normal signature corresponding to the condition signature for the machinery without bearing anomalies;

comparing the condition signature with the normal signature; and

registering a bearing anomaly if the condition signature differs from the normal signature by more than a predetermined threshold.

5. A method according to claim 4, wherein the normal signature is predicted from a model defining one or more inter-dependencies between the condition indicators.

6. A method according to claim 5, wherein the model is a learnt model.

7. A method according to claim 5, wherein the model comprises a matrix with one or more non-zero off-diagonal terms to define said inter-dependencies.

8. A method according to claim 7, wherein the step of comparing the condition signature with the normal signature involves calculating a value for the normalised innovations squared.

9. A method according to claim 5, wherein the model comprises a neural network.

10. A method according to claim 9, wherein the step of comparing the condition signature with the normal signature involves calculating a prediction error.

11. A method according to any one of claim 4, wherein said times define successive intervals of at most 1 sec duration.

13. A data processing system for locating bearing anomalies in machinery, comprising:

a data receiver for receiving vibration measurements acquired from the machinery, and

a processor for (a) analysing the vibration measurements to identify novel tracked orders indicative of bearing anomalies, and (b) ascertaining the location of a bearing anomaly by relating a novel tracked order thus-identified to one or more further tracked orders.

14. A data processing system for detecting bearing anomalies in machinery, comprising:

data acquisition devices for acquiring a plurality of condition indicators from the machinery at each of a plurality of times, the condition indicators including (a) a plurality of vibration measurements or (b) one or more vibration measurements and one or more performance parameter measurements;

a processor for constructing a condition signature from said vibration measurements and for predicting a normal signature corresponding to the condition signature for the machinery without bearing anomalies;

a comparator for comparing the condition signature with the normal signature; and

a register for registering a bearing anomaly if the comparator indicates that the condition signature differs from the normal signature by more than a predetermined threshold.