WAVELET-BASED ANALYSIS FOR FOULING DIAGNOSIS OF AN AIRCRAFT HEAT EXCHANGER

• US 20160305865A1
• Filed: 04/17/2015
• Published: 10/20/2016
• Est. Priority Date: 04/17/2015
• Status: Active Grant

• Current Assignee: Hamilton Sundstrand Corporation (Rtx Corporation), University of Connecticut (State of Connecticut)
• Original Assignee: Hamilton Sundstrand Corporation (Rtx Corporation)
• Inventors: Silva, Andre A., Najjar, Nayeff A., Gupta, Shalabh, D'Orlando, Paul M., Walthall, Rhonda Dawn
• Granted Patent: US 10,288,548 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: F28F 27/00 Control arrangements or safety devices specially adapted for heat-exchange or heat-transfer apparatus control arrangements in general G05
• CPC Class Codes: G01N 17/008 Monitoring fouling
• CPC Class Codes: G01N 25/18 by investigating thermal conductivity by calorimetry G01N25/20; by measuring change of resistance of an electrically-heated body G01N27/18

Abstract

A method and apparatus for estimating a fouling state of a heat exchanger of an aircraft. Training sensor measurements are obtained of a parameter related to operation of the heat exchanger and a wavelet transform is applied to the training sensor measurements to obtain wavelet data. Data reduction is performed on the wavelet data to obtain representative features indicative of the training sensor measurements. A classifier is then trained to assign suitable fouling classes to the representative features. The trained classifier is used on testing sensor measurements from the heat exchanger to assign a fouling class to the testing sensor measurements in order to estimate the fouling state of the heat exchanger.

Claims

1. A method of estimating a fouling state of a heat exchanger of an aircraft, comprising:

obtaining training sensor measurements of a parameter related to operation of the heat exchanger;

applying a wavelet transform to the training sensor measurements to obtain wavelet data;

performing data reduction on the wavelet data to obtain a representative feature indicative of the training sensor measurements;

training a classifier to assign a suitable fouling class to the representative feature; and

applying the trained classifier to testing sensor measurements from the heat exchanger to assign a fouling class to the testing sensor measurements in order to estimate the fouling state of the heat exchanger.

2. The method of claim 1, wherein the heat exchanger is included in an environmental control system having an air cycle machine, and the parameter further comprises at least one of:

(i) heat exchanger output temperature;

(ii) condenser inlet temperature;

(iii) Environmental Control System output temperature;

(iv) Environmental Control System input pressure; and

(v) an angular speed of an Air Cycle Machine.

3. The method of claim 1, wherein the fouling class of the heat exchanger is known a priori.

4. The method of claim 3, further comprising classifying the representative feature using a pattern classification algorithm.

5. The method of claim 4, wherein training the classifier further comprises applying a cross-validation algorithm to test the ability of the classifier to correctly classify the representative feature.

6. The method of claim 1, further comprising obtaining the training sensor measurements from a model of the heat exchanger under different fouling conditions.

7. The method of claim 6, wherein training the classifier further comprises establishing fouling classification categories.

8. The method of claim 1, further comprising evaluating a performance of the classifier to reduce a number of false alarms and missed detections.

14. The apparatus of claim 8, wherein the processor is further configured to train the classifier using the model of the heat exchanger under different fouling conditions.

15. The apparatus of claim 8, wherein training the classifier further comprises establishing fouling classification categories.

9. An apparatus for estimating a fouling state of a heat exchanger of an aircraft, comprising:

a model of the heat exchanger;

one or more sensors configured to obtain training sensor measurements of a parameter related to an operation of the model of the heat exchanger; and

a processor configured to;

apply a wavelet transform to the training sensor measurements to obtain wavelet data;

perform data reduction on the wavelet data to obtain a representative feature,

train a classifier to assign a suitable fouling class to the representative feature, and

apply the trained classifier to testing sensor measurements from the heat exchanger to assign a fouling class to the testing sensor measurements in order to estimate the fouling state of the heat exchanger.

10. The apparatus of claim 9, wherein the heat exchanger is included in an Environmental Control System having an air cycle machine and the parameter further comprises at least one of:

(i) heat exchanger output temperature;

(ii) condenser inlet temperature;

(iii) Environmental Control System output temperature;

(iv) Environmental Control System input pressure; and

(v) an angular speed of an air cycle machine.

11. The apparatus of claim 9, wherein the processor is further configured to estimate the fouling state by performing a pattern classification algorithm on the representative feature to classify the representative feature.

12. The apparatus of claim 9, wherein the fouling class of the heat exchanger is known a priori.

13. The method of claim 12, wherein training the classifier further comprises applying a cross-validation algorithm to test the ability of the classifier to correctly classify the representative feature.