Adding Sensor Diagnostics into a Prognostics Model to Better Predict End of Life Gearbox...

Adding Sensor Diagnostics into a Prognostics Model to Better Predict End of Life Gearbox Projections

October 15, 2014

Model-based, multi-physics based prognostics computational technologies

and services

Our applications help extend the remaining useful life (RUL) of new and existing

mechanical systems

The newest prognostics health management (PHM) application for

condition-based maintenance (CBM)

Sentient Science is Based on Three Fundamental Capabilities

April 15, 2023

Adding Sensor Diagnostics Into a Prognostics Model

Our 10 Year Research Pedigree Invited a New way to Measure and Test Rotating Equipment Computationally

DEPARTMENT OF DEFENSE

DEPARTMENT OF ENERGY

NATIONAL SCIENCE FOUNDATION

Adding Sensor Diagnostics Into a Prognostics ModelApril 15, 2023

Sentient Science Family

April 15, 2023


Sentient Science InnovationExtend the remaining useful life (RUL) through prognostics

Use sensors predicatively rather than diagnostically to operational failure

Sentient Science InnovationExtend the remaining useful life (RUL) through prognostics

Use sensors predicatively rather than diagnostically to operational failure

B – Crack Initiation

Gap between current diagnostic state D and future prognostic state

C.

Extended Life through

prognostics

A – Asset enters service

D – Operational Failure

C - Failure can be confidentlypredicted - PROGNOSIS

®

April 15, 2023


DigitalClone®

Nucleation & PropagationToo Late

Adding Sensor Diagnostics Into a Prognostics ModelApril 15, 2023

Sentient’s Prognostics + Sensor Diagnostics = Model Data Fusion

Technical Approach and Advantages

April 15, 2023


Definitions

• CBM Value Statement: Tells you what turbine has started to operationally fail with a few months warning.

– Sensors used to provide additional condition status updates on top of control system sensors

• Prognostics (PHM) Value Statement: What can you do now to keep it from failing?

– Only already installed control system sensors are needed to know failure risk levels

– CBM system sensors are used to identify which turbine at risk will fail

• What is CBM?– Tool that provides feedback on the condition status of a system/component– Typically done through vibration analysis (past 60+ years) or oil debris

sensors (past 50+ years)– Allows you to know 1-6 months advanced notice of failure

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Current State of Vibration Analysis

• High Cost (Upfront, High Number of Sensors)– Number of required sensors unknown– “Over-Sensored”– No upfront optimization

• High Amounts of Data Required (How do you identify a failure?)– Need to see failures with your system– Massive amounts of data before identification of failure– End up with too little or too much data

• Large Amounts of Time Dedicated To Monitoring– Hard to automate until failures are seen in data– Hard to set standard alarm levels, not all “identical” failures look

the same

+ ???

w/o Prognostics

w/ Prognostics

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1. To provide the same or better accuracy on predictions of component or system failures on a gearbox than traditional CBM alone

• Better interpretation of the sensor signal• Better serialized DigitalClone model for a specific fielded asset

2. To use sensors predictively rather than diagnostically• Using our sensor to validate our prediction for a serialized

asset and to know if we need to recalculate our predictions based on operating conditions

• Sensor is used as an extension to our data model

3. To lower the cost of the sensor infrastructure• Data model indicates the location of potential failure so that we

can target the number and position of the sensors on the gearbox

Sentient’s Prognostics + Sensors

April 15, 2023


The Conventional approach assumes an ideal system with precisely defined parameters which determines the value of the system level output.

Physics-based

Model: ẋ=f(x,p)

Parameters

External ForcesOutput

Prognostics vs. Diagnostics - only Approach

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Sentient innovative approach based on Model Data Fusion (MDF) for better serialized operational failure prediction

- The MDF approach considers the manufacturing tolerances, and reduces the uncertainty in parameters by fusing measurements with a dynamic model. - Decreases the uncertainty bounds in the life estimation of a

component

Physics-based Model: ẋ=f(x,p)

Parameters

External Forces

OutputParameter and Force Estimator

Initial values

Measurem

ents

Prognostics vs. Diagnostics - only Approach

April 15, 2023


Prognostics + Diagnostics Red LevelDefinition

Level Operational RUL DefinitionRed in DCL No Change, 12 month or less

RUL, Sensor plus prognostic model

Red Severity 1 12 Months Least severe critical forces seen - Excitation forces seen 1.16 x 104 N (Newton’s) above the 8.0 x 104 N level

Red Severity 2 8 Months 2nd Least severe critical forces seen - Excitation forces seen 2.32 x 104 N above the 8.0 x 104

N level

Red Severity 3 3 Months 2nd Most severe critical forces seen -Excitation forces seen 2.90 x 104 N above the 8.0 x 104 N level

Red Severity 4 1.5 Months Most severe critical forces seen - Excitation forces seen 3.50 x 104

N above the 8.0 x 104 N level

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DigitalClone LIVE

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Vibration Reports

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Sentient’s Prognostics + Sensor Model = Model Data Fusion

Applications, Demonstration – Wind Examples

Gearbox Operational FailureUptower ReplacementsDerate/Uprate Effects

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Prognostics + Sensors Gearbox Failure Prediction

0 5 10 15 20 25 30 35 400

1

2

3

4

5

6

7

8

9

10x 10

4

Mean

Value

Alert to consistent jump in excitation force

Condit

ion

Indic

ato

r

December, 2014 SeptemberAugust, 2014

DigitalClone identified gearbox failure months in

advance

Magnitude of excitation force due to a spalled intermediate pinion tooth

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14.8 15 15.2 15.4 15.6 15.8 16

3

4

5

6

7

8

9

x 104

Damaged Gearbox

Healthy Gearbox

SPEED (RPM)

Cond

ition

Indi

cato

r

14.8 15 15.2 15.4 15.6 15.8

2

3

4

5

6

7

8

9

x 104

SPEED (RPM)

Damaged Gearbox

Healthy Gearbox

Cond

ition

Indi

cato

r

Sentient DigitalClone sensor accurately estimated the health state of a faulted gearbox and healthy gearbox

Prognostics + Sensors Gearbox Failure Prediction

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Turbine 01 April 2014 - High Risk Turbine, red alert

• Critical components: low speed pinion, cylindrical bearing

Turbine 02April 2014 - High Risk Turbine , red alert

• Critical components: low speed pinion

Turbine 01 June 2014 (1.0 MW) - Low Risk Turbine , yellow alert

• Critical components: LSP• OVERALL IMPROVEMENT IN GEARBOX OPERATION

July 2014 (1.75MW) - High Risk Turbine , orange alert• Critical components: Bull Gear, Int. LSP, MSBRG• CONTINUING DAMAGE PROGRESSION SEEN

Turbine 02 July 2014 (1.5MW) - Low Risk Turbine and a yellow alert

• Critical components: Int. LSP, MSBRG, ISBRG• OVERALL IMPROVEMENT IN GEARBOX OPERATION

BEFOREREPLACEMENT

AFTERREPLACEMENT

Prognostics + Sensors Gearbox Uptower Replacement, Derate/Uprate Effect

April 15, 2023


Prognostics + Sensors Gearbox Uptower Replacement (BEFORE REPLACEMENT)

• Red Alert: High Risk Turbine• Sensor simulations show continuing high risk, especially the intermediate LSP, Downwind MSBRG, and Upwind ISBRG• If CI values, high excitation forces, are consistently much above 8.0e+04 – Red Alert

14.9 15 15.1 15.2 15.3 15.4 15.5 15.6 15.7 15.89

9.5

10

10.5x 10

4

14.9 15 15.1 15.2 15.3 15.4 15.5 15.6 15.7 15.89

9.5

10

10.5x 10

4

Downwind MSBRG

Upwind ISBRG

Red Alert

Red Alert

Simulation Dates: April 2014Simulation Dates: April 2014

14.9 15 15.1 15.2 15.3 15.4 15.5 15.6 15.7 15.86

7

8

9

10x 10

4 CI10 vs. Speed

14.9 15 15.1 15.2 15.3 15.4 15.5 15.6 15.7 15.80

5

10x 10

4 CI12 vs. Speed

Bull Gear

Intermediate Pinion (LSP)

Red Alert

Red Alert

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Simulation Dates: Late June 2014After bearing replacement

10.95 11 11.05 11.1 11.153.5

4

4.5

5x 10

4

10.95 11 11.05 11.1 11.153.5

4

4.5

5x 10

4

Downwind MSBRG

Upwind ISBRG

Yellow Alert

Yellow Alert

• Yellow Alert: Low Risk Turbine• Sensor simulations show new low risk in the Gears & Bearings, with slight elevations in the intermediate LSP• If CI values, excitation forces, are consistently much above 4.5e+04 – Yellow Alert• Improved linearity and consistency seen, indicative of healthier operation.

Simulation Dates: Late June 2014After bearing replacement

10.8 10.85 10.9 10.95 11 11.05 11.1 11.154.75

4.8

4.85

4.9

4.95x 10

4 CI10 vs. Speed

10.8 10.85 10.9 10.95 11 11.05 11.1 11.154

4.5

5

5.5

6x 10

4 CI12 vs. Speed

Bull Gear

Intermediate Pinion (LSP)

Orange Alert

Yellow Alert

Elevated forces at higher speeds

Overall improvement in gearbox operation

Prognostics + Sensors Gearbox Uptower Replacement (AFTER REPLACEMENT)

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Sentient’s Prognostics + Sensor ModelBenefits Summary

• If you already have CBM, Prognostics will provide asset life assessments 1-10 years going forward

• If you do not have CBM today, Model Data fusion between the prognostics (multi-physics model) and the CBM sensor (oil, vibration, other) will provide a highly accurate solution for 1-12 month operational failure

• Prognostics tell you what component will fail and when. The sensor (using MDF approach) is used to confirm predictions instead of waiting for imminent failure

April 15, 2023


Adding Sensor Diagnostics into a Prognostics Model to Better Predict End of Life Gearbox Projections

October 15, 2014

Adding Sensor Diagnostics into a Prognostics Model to Better Predict End of Life Gearbox...

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