# US 2015/0106313 A1 · Predictive modeling of high-bypass turbofan engine deterioration

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- Number: US 2015/0106313 A1
- Document ID: US20150106313A1
- Status: Published application
- Kind: A1
- Application number: 14/512,159
- Filed: 2014-10-10
- Published: 2015-04-16
- Earliest claimed: 2013-10-11
- Assignees: General Electric Company
- Applicants: General Electric Company
- Inventors: Neil Holger White Eklund; Mohak Shah; Daniel Edward Marthaler; Christina Marie Brasco
- Web page: https://patentgrep.com/patent/US20150106313A1

## CPC

- G06N 3/02: Neural networks
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

A method, medium, and system to receive actual operational flight data for an engine of a particular type and configuration; train a neural network to generate an indicator of the health of the engine based on multiple different inputs to the neural network at a time the flight data was acquired; determine a deterioration factor for the engine, based at least in part, on an operational climate for the engine; and provide a record of the determined deterioration factor.

## Claims

### Claim 1

A method, the method comprising:
receiving actual operation flight data for an engine of a particular type and configuration;
training a neural network to generate an indicator of the health of the engine based on multiple different inputs to the neural network at a time the flight data was acquired;
determining a deterioration factor for the engine, based at least in part, on an operational climate for the engine; and
providing a record of the determined deterioration factor.

### Claim 2 (depends on 1)

The method of claim 1, wherein the engine comprises a high-bypass turbofan engine.

### Claim 3 (depends on 1)

The method of claim 1, wherein the health of the engine is indicated by an exhaust gas temperature parameter for the engine.

### Claim 4 (depends on 1)

The method of claim 1, wherein the multiple different inputs to the neural network include at least a bleed ratio, a Mach number, a percentage of maximum fan speed of the engine, ambient temperature, and altitude.

### Claim 5 (depends on 1)

The method of claim 1, wherein the climate is determined to be at least one of the following different climates: tropical/equatorial, dry, mild temperate, continental/microthermal, and polar.

### Claim 6 (depends on 1)

The method of claim 1, wherein the deterioration factor is determined on a basis of an airline operator.

### Claim 7

A non-transitory medium storing processor-executable program instructions, the medium comprising program instructions executable by a computer to:
receive actual operation flight data for an engine of a particular type and configuration;
train a neural network to generate an indicator of the health of the engine based on multiple different inputs to the neural network at a time the flight data was acquired;
determine a deterioration factor for the engine based, at least in part, on an operational climate for the engine; and
provide a record of the determined deterioration factor.

### Claim 8 (depends on 7)

The medium of claim 7, wherein the engine comprises a high-bypass turbofan engine.

### Claim 9 (depends on 7)

The medium of claim 7, wherein the health of the engine is indicated by an exhaust gas temperature parameter for the engine.

### Claim 10 (depends on 7)

The medium of claim 7, wherein the multiple different inputs to the neural network include at least a bleed ratio, a Mach number, a percentage of maximum fan speed of the engine, ambient temperature, and altitude.

### Claim 11 (depends on 7)

The medium of claim 7, wherein the climate is determined to be at least one of the following different climates: tropical/equatorial, dry, mild temperate, continental/microthermal, and polar.

### Claim 12 (depends on 7)

The medium of claim 7, wherein the deterioration factor is determined on a basis of an airline operator.

### Claim 13

A system comprising:
a computing device comprising:
a memory storing processor-executable program instructions; and
a processor to execute the processor-executable program instructions to cause the computing device to:
receive actual operational flight data for an engine of a particular type and configuration;
train a neural network to generate an indicator of the health of the engine based on multiple different inputs to the neural network at a time the flight data was acquired;
determine a deterioration factor for the engine, based at least in part, on an operational climate for the engine; and
provide a record of the determined deterioration factor.

### Claim 14 (depends on 13)

The system of claim 13, wherein the engine comprises a high-bypass turbofan engine.

### Claim 15 (depends on 13)

The system of claim 13, wherein the health of the engine is indicated by an exhaust gas temperature parameter for the engine.

### Claim 16 (depends on 13)

The system of claim 13, wherein the multiple different inputs to the neural network include at least a bleed ratio, a Mach number, a percentage of maximum fan speed of the engine, ambient temperature, and altitude.

### Claim 17 (depends on 13)

The system of claim 13, wherein the climate is determined to be at least one of the following different climates: tropical/equatorial, dry, mild temperate, continental/microthermal, and polar.

### Claim 18 (depends on 13)

The system of claim 13, wherein the deterioration factor is determined on a basis of an airline operator.