Plate-fin heat exchanger fouling identification

Patent metadata

Field	Value
Publication number	US-10495547-B2
Application number	US-201615168741-A
Country	US
Kind code	B2
Filing date	May 31, 2016
Priority date	Jun 8, 2015
Publication date	Dec 3, 2019
Grant date	Dec 3, 2019

Abstract

A computer-implemented method for designing a built-in test is described. The method includes receiving, via a processor, a subsystem model including system parameters for a heat exchanger, wherein each of the system parameters includes a sensor variance; determining, via the processor, a test design vector based on one or more of the system parameters; and designing, via the processor, the built-in test based on the test design vector.

First claim

What is claimed is:

1. A computer-implemented method for designing and operating a built-in test (BIT) comprising:
receiving, via a processor, a subsystem model for a heat exchanger, the model including system parameters for inputs for the heat exchanger, wherein each of the inputs is limited to variation between upper and lower bounds and can be measured by a sensor having a sensor variance;
determining, via the processor, a test design vector based on one or more of the system parameters, wherein determining includes assessing an input uncertainty;
assessing, via the processor, the sensor variance for each of the inputs;
assessing, via the processor, a system model error;
designing, via the processor, the built-in test based on the test design vector; and
applying the BIT to an aircraft based on at least an inlet bleed temperature that the BIT causes the aircraft to increase by at least one discrete step during the test to determine fouling in the heat exchanger.

2. The computer-implemented method of claim 1 , wherein the system parameters comprise a thermal fouling resistance, a moisture content, an inlet pressure and a mass flow.

3. The computer-implemented method of claim 1 , further comprising:
determining, via the processor, a precision value for the designed built-in test;
comparing, via the processor, the precision value for the designed built-in test with a predetermined precision threshold benchmark; and
redesigning, via the processor, a second built-in test responsive to determining that the precision value does not meet or exceed the predetermined precision threshold benchmark.

4. The computer-implemented method of claim 3 , wherein redesigning the second built-in test comprises altering, via the processor, at least one sensor variance.

5. A computer program product for designing and operating a built-in test (BIT), the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor operatively connected to at least one sensor to cause the processor to perform a method comprising:
receiving, via the processor, a subsystem model for a heat exchanger, the model including system parameters for inputs for the heat exchanger, wherein each of the inputs is limited to variation between upper and lower bounds and can be measured by a sensor having a sensor variance;
determining, via the processor, a test design vector based on one or more of the system parameters, wherein determining includes assessing an input uncertainty;
assessing, via the processor, the sensor variance for each of the inputs;
assessing, via the processor, a system model error;
designing, via the processor, the built-in test based on the test design vector; and
applying the BIT to an aircraft based on at least an inlet bleed temperature that the BIT causes the aircraft to increase by at least one discrete step during the test to determine fouling in the heat exchanger.

6. The computer program product of claim 5 , wherein the system parameters comprise a thermal fouling resistance, a moisture content, an inlet pressure and a mass flow.

7. The computer program product of claim 5 , further comprising
determining, via the processor, a precision value for the built-in test;
comparing, via the processor, the precision value for the built-in test with a predetermined precision threshold benchmark; and
redesigning, via the processor, a second built-in test responsive to determining that the precision value does not meet or exceed the predetermined precision threshold benchmark.

8. The computer program product of claim 7 , wherein redesigning the second built-in test comprises altering, via the processor, at least one sensor variance.

9. A computer-implemented method for designing and operating a built-in test (BIT) comprising:
receiving, via a processor, a subsystem model for a heat exchanger, the model including system parameters for inputs for the heat exchanger, wherein each of the inputs is limited to variation between upper and lower bounds and can be measured by a sensor having a sensor variance;
determining, via the processor, a test design vector based on one or more of the system parameters, wherein determining includes assessing an input uncertainty and assessing, via the processor, the sensor variance for each of the inputs;
designing, via the processor, the built-in test based on the test design vector; and
applying the BIT to an aircraft based on at least an inlet bleed temperature that the BIT causes the aircraft to increase by at least one discrete step during the test to determine fouling in the heat exchanger.

Assignees

• Hamilton Sundstrand Corp

Inventors

• Bollas George M
• Palmer Kyle
• Prasad Dilip
• Jacobson Clas A
• Maljanian Jr John M
• Poisson Richard A
• Park Young K

Classifications

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title

• G06F30/15

  Vehicle, aircraft or watercraft design · CPC title

• G06F30/17 Primary

  Mechanical parametric or variational design · CPC title

• G05B23/0254

  based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks · CPC title

• G01M99/005 Primary

  Testing of complete machines, e.g. washing-machines or mobile phones (testing of machine parts G01M13/00; testing of electric apparatus or components G01R31/50) · CPC title