Research Community’s Perspective to Streamline Engine ...

Dr Yi-Guang Li PhD, MSc, BSc, ASME Fellow

Reader in Gas Turbine Technology

School of Aerospace, Transport and Manufacturing, Cranfield University, UK

24th ISABE Conference

Short Course

RAeS-IMechE Seminar on MRO Crisis:

Challenges and Opportunities

(26th November 2019)

Research Community’s Perspective to Streamline Engine Maintenance

Gas Turbine Engine Degradation

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Courtesy of Rolls-Royce

Pro

bab

ility

of

Failu

re

Time to Failure Average Time to Failure

Life given to Users

Unfavourable operating

environment

Favourable operating

environment

• Fouling

• Corrosion

• Erosion

• FOD

• Tip clearance damage

• etc.

Maintenance Strategies

Corrective Maintenance (Run to failure)

Preventive Maintenance (Time-Scheduled)

Predictive Maintenance (Condition-Based)

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Condition monitoring is the supporting technology

Integrated Condition Monitoring Systems

Integrated Condition Monitoring

system

Oil analysis and

debris monitoring Vibration

Monitoring

HPT Temperature

entry spread

Gas Path

Monitoring

Limited

Transient

Monitoring

Visual

Inspection

Life

Consumption

Monitoring

Degradation & Failure Prediction

Exhaust

Temperature

monitoring

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Digital Twins for Operation and

Maintenance

Digital twins – computerized companion of physical asset that can

be used for various purposes (Wikipedia):

- Performance modelling

- Condition monitoring

- Remote operation & control

- Condition based maintenance

Courtesy of Rolls-Royce

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Performance Adaptation

(towards digital twins)

Pe

rfo

rma

nce

Real

Simulated

Ambient and Operating Conditions

Pe

rfo

rma

nce

Real

Ambient and Operating Conditions

Simulated

Design-Point (DP) adaptation

Off-Design (OD) adaptation

Li Y.G., Pilidis P. and Newby M., “An Adaptation Approach for Gas Turbine Design-Point Performance Simulation”, ASME Journal of Engineering for Gas Turbine and Power,

Vol. 128, pp.789-795, October 2006.

Li, Y.G., Abdul Ghafir M.F., Wang L., Singh R., Huang K., Feng X. and Zhang W., “Improved Multiple Point Non-Linear Genetic Algorithm Based Performance Adaptation

Using Least Square Method”, ASME Journal of Engineering for Gas Turbines and Power, Vol. 134, pp.031701, March 2012. 6

Performance Adaptation

(towards digital twins)

Design Point (DP) Adaptation Off-design (OD) Adaptation

Errors before OD adaptation

Errors after OD adaptation

Test Data

Errors at DP after DP adaptation

Application of Performance Adaptation to GE LM2500+ Engine in Manx Utilities,

Isle of Man, UK

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Engine Health Monitoring

- Gas Path Diagnostics & Prognostics

To detect and/or forecast engine gas path component degradation

or faults using gas path measurements

Li Y.G. and Singh R., “An Advanced Gas Turbine Gas Path Diagnostic System - PYTHIA”, ISABE-2005-1284, the Seventeenth International

Symposium on Airbreathing Engines (17th ISABE), Munich, Germany, September 2005.

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Gas Path Analysis (GPA) Artificial Neural Networks Genetic Algorithms Expert Systems Data driven …………………..

Engine Health Monitoring

- Gas Path Diagnostics & Prognostics

Engine Model

Data Acquisition & Correction

Measurement Selection

Sensor Fault Diagnostics

Component Diagnostics

Model Performance Adaptation

Results

Courtesy of Rolls-Royce

Measurement data

Measurement data

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Engine Prognostics

Engine Health Monitoring

- Gas Path Diagnostics

Pythia Software Application:

CCGT power plant using two GE

LM2500+ engines at Manx Utilities in

the UK

Pythia performance and diagnostic

system/software for condition

monitoring of gas turbine engines

Blinstrub J., Li Y.G., Newby M., Zhou Q., Stigant G., Pilidis, P. and Honen H., “Application of Gas Path Analysis to Compressor Diagnosis

of an Industrial Gas Turbine Using Field Data”, GT2014-25330, ASME TURBO EXPO 2014, Dusseldorf, Germany, June 2014.

Courtesy of Manx Utilities, Isle of Man, UK

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Performance Status Monitoring

xhz

Turbine Entry Temperature

Engine mass flow rate

Compressor PR, Eff.

Bypass ratio

Turbine Eff.

Cooling flows

Fuel flow rate

Thrust / Power

Pressures

Temperatures

Shaft speeds

Courtesy of Rolls-Royce

Performance parameters: Gas path measurements

Li, Yi-Guang, “Aero Gas Turbine Flight Performance Estimation Using Engine Gas Path Measurements”, AIAA Journal of

Propulsion and Power, Vol. 31, No. 3, May-June 2015. 11

Performance Status Monitoring

Model aero gas turbine similar to EJ200 turbofan

Performance specification comes from open literature

Cranfield Pythia software is used to build up the performance model

Performance estimation method is implemented into Pythia

Performance Estimation for Engine at Flight (H = 8km) - Degraded performance

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Creep Life Consumption Monitoring

Condition parameters

Life Estimation model

Stress model

Thermal model

Creep model

Reference operating condition

Creep Factor

RefLc

LcCF

Creep Factor

𝐿𝑐 - Creep life

1FCPresent condition creep life is equivalent to the life at ref. condition

1FCEngine is operated at a better condition thus increasing the creep life

1FC Engine is operated at a much worse condition thus reducing the creep life

Abdul Ghafir M.F., Li Y.G., Wang L. and Zhang W., “Impact Analysis on Aero-Engine Performance Parameter Variation on Hot Section’s

Creep Life Using Creep Factor Approach”, ISABE-2011-1609, 20th ISABE Conference, Gothenburg, Sweden, 12-16 September 2011. 13

Creep Life Consumption Monitoring

Creep life consumption monitoring for a helicopter engine

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Equivalent Operating Time (EOT) and

Remaining Useful Life (RUL)

Degradation Equivalent Operating Time (EOT)

𝐸𝑂𝑇 = 𝐷

𝐷 𝑟𝑒𝑓× 𝑡

• Degradation EOT is a converted operating time for an engine or its components.

• It expresses engine component performance degradation relative to a reference operating condition.

𝐸𝑂𝑇 = 𝐸𝑂𝑇 𝑓𝑎𝑐𝑡𝑜𝑟 × 𝑡

𝐷 = Component health degradation 𝐷 = Degradation rate at current operating condition

𝐷 𝑟𝑒𝑓 = Degradation rate at reference condition

𝑡 = Actual operating time spent at this condition.

𝐸𝑂𝑇 𝑓𝑎𝑐𝑡𝑜𝑟 = 1 +𝐷 𝑓 + 𝐷 𝑒 + 𝐷 𝑥

𝐷 𝑟𝑒𝑓+ 𝛼 ∙

𝐷 𝐶

𝐷 𝐶.𝑟𝑒𝑓

𝑓 = Fouling 𝑒 = Erosion 𝑥 = Additional degradation mechanism 𝑐 = Creep strain. 𝛼 = Contribution of blade creep strain to tip wear and performance loss

where:

Alozie O, Li Y.G., Diakostefanis M., Wu X., Shong X. and Ren W., “Assessment of Degradation Equivalent Operating Time for Aircraft Gas Turbine

Engines”, ISABE-2009-24419, the Twenty-Fourth International Symposium on Airbreathing Engines (24th ISABE), Canberra, Australia, September 2019. 15

Equivalent Operating Time (EOT)

and Remaining Useful Life (RUL)

Flight Mission: Altitude, Mach number and Fan Speed vs. Flight Time

Tip rub starts

Tip rub stops

RUL Prediction

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How Can Condition Monitoring Benefit us?

Investment

Cost Saving

Net Saving (ROI)

Loss

Loss

Condition Monitoring System Complexity

Mo

ney

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Summary

New technologies offer potentials to streamline engine operation and maintenance and meet MRO challenges:

- Moving from preventive (scheduled) maintenance to predictive (condition-based) maintenance

- Condition monitoring & Digitalization (digital twins) are two of the key technologies

Optimal use of the technologies to get maximum return of investment

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