Download - Wind Turbine Drivetrain Condition Monitoring · 2013. 10. 1. · Gearbox Reliability Collaborative (Cont.) 8 Technical Approach •Modeling and analysis •Dynamometer test •Field

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Wind Turbine Drivetrain Condition Monitoring

Shuangwen (Shawn) Sheng Senior Engineer, NREL/NWTC

CREW Seminar Series October 7, 2011

Boulder, CO

NREL/PR-5000-52908

NATIONAL RENEWABLE ENERGY LABORATORY

Outline

Introduction Drivetrain Condition Monitoring Tests Results and Discussions Concluding Remarks

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DOE

1.5

MW

Win

d Tu

rbin

e /P

IX17

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Introduction

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A typical utility-scale wind turbine

Global Wind Energy – Then and Now

Wind Turbine Gearbox Reliability Challenge

Gearbox Reliability Collaborative (GRC)

A typical Condition Monitoring (CM) system

Benefits of machine CM

CM under the GRC

Cost justification of wind turbine CM


A typical utility-scale wind turbine

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Turbine • Foundation • Tower • Nacelle • Hub • Blades

Test

Tur

bine

s at N

REL/

PIX1

8937

Nacelle • Main bearing • Main shaft • Gearbox • Brake • Generator shaft • Generator • Yaw and pitch systems

(not illustrated)


Global Wind Energy - Then and Now [1]

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Wind Turbine Gearbox Reliability Challenge

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Gearboxes do not always achieve their 20-year design life

Premature failure of gearboxes increases

the cost of energy • Turbine downtime • Unplanned maintenance • Gearbox replacement and rebuild • Increased warranty reserves

The problem • Is widespread • Affects most original equipment manufacturers (OEMs) • Is not caused by manufacturing practices


Gearbox Reliability Collaborative (GRC)

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Facilitate dialog among all parties • Designers and consultants • Suppliers and rebuilders • Operations and maintenance organizations

Understand gearbox response to specific loading • Pure torque, bending, thrust (dynamometer) • Turbulence (field)

Understand the physics of premature wind turbine gearbox failure

Identify gaps in design process

Suggest improvements in design practices and analytical tools


Gearbox Reliability Collaborative (Cont.)

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Technical Approach • Modeling and

analysis • Dynamometer test • Field test • Failure database • Condition monitoring

Goal • To improve gearbox

reliability and increase turbine uptime, which in turn will reduce the cost of energy

Field Test Dynamometer Test • Test plan • Test article • Test setup & execution

• Test plan • Test turbine • Test setup & execution

Analysis • Load cases • System loads • Internal loads

Test

Tur

bine

at N

REL/

PIX1

9022

NREL Dynamometer/PIX16913


A typical Condition Monitoring System[2]

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Physical Measurement: convert measured physical symptoms, typically to electrical signals

Data Acquisition: data transmission from sensors to processing unit

Feature Extraction: extract characteristic information from raw sensor data

Pattern Classification: diagnosis of defect type and severity level Life Prediction: prognosis of remaining service life of the

monitored structure.

Monitored Structure

Physical Measurement

Feature Extraction

Data Acquisition

Pattern Classification

Life Prediction

Vibr

ation

Leve

l Bearing Failure

Alarm Trigger

Healthy ThresholdVibr

ation

Leve

l Bearing Failure

Alarm Trigger

Healthy Threshold


Benefits of Machine CM

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Early deterioration detection to avoid catastrophic failure

Accurate damage evaluation

to enable a cost-effective maintenance practices

Root cause analysis to

recommend improvements in component design or equipment operation and control strategy.

Test

Tur

bine

at P

onne

quin

/PIX

1925

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Condition Monitoring under the GRC

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The main deliverable from the GRC: improved gearbox design and modeling practices • Helps the industry as a whole • Provides no information on individual

turbine health condition

Health Monitoring • Helps provide individual turbine

health information and increase turbine uptime

• Condition monitoring (CM) for drivetrain (gearbox, generator, and main bearing) and structural health monitoring (SHM) for rotor

Test

Tur

bine

at N

REL/

PIX1

9022


Cost Justification of Wind Turbine CM

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Return on Investment for all three cases less than 3 years

Based on 1.5 MW wind turbine with replacement costs of about €150,000 for gearbox, €38,000 for a generator and €25,000 for a main bearing (DEWI)

Costs for planned repair < 30% for unplanned replacement (DEWI) Cost per CM system approximately €5,000 plus €1,000 per year per wind

turbine (service) Above cost savings do not include loss of production

Operator / Owner

# of Turbines Duration of Service

Costs CMS plus Service in €

Detected Damages Costs unplanned Replacement Costs planned Repair in €

Total Savings in €

enviaM 15 WTG‘s 5 years

150,000 3 x Gearbox 405,000 101,250

303,750 In 5 years

e.disnatur 130 WTG‘s 5 years

1,300,000 12 x Gearbox 40 x Generator bearing

4,620,000 1,155,000

3,465,000 In 5 years

juwi Management

59 WTG‘s 3 years

472,000 20 x Gearbox 1 x Generator bearing 1 x Main bearing

2,811,000 702,750

2,108,250 In 3 years

Experience at Schenck [3]


Drivetrain Condition Monitoring

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Downtime caused by Turbine Subsystems

Typical CM Practices

GRC CM Approach and Rationale


Downtime Caused by Subsystems

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Data Source: Wind Stats Newsletter, Vol. 16 Issue 1 to Vol. 22 Issue 4, covering 2003 to 2009[4]

Based on the data reported to Wind Stats for the first quarter of 2010, the data represents: about 27,000 turbines, ranging from 500 kW to 5 MW.

Top Three: 1. Gearbox 2. Generator 3. Electric Systems

Consider crane cost: • Main bearing also needs

attention • Electric systems often do

not need an expensive crane rental.


Typical Drivetrain CM Practices

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Techniques • Acoustic emission (e.g.,

stress wave) analysis • Vibration analysis • Oil debris analysis

Typical Practices • Integration of vibration or

stress wave with oil debris analysis

Sample Vibration Spectra[5]

Sample Oil Debris Counts[5]


GRC CM Approach and Rationale

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Integrated Approach • Acoustic emission (stress wave) • Vibration analysis • Oil debris and condition monitoring techniques • Electric signature-based technique

Rationale • No single technique can detect all possible failure modes seen in

wind turbines • Each technique has its own strengths and limitations • Combine active machine wear detection capability of lubrication

oil monitoring techniques with crack location pinpointing capability of AE and vibration analysis

• Investigate potential technique for direct-drive turbines


Tests

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NREL 2.5-MW Dynamometer

Test Articles

Dynamometer Test Setup

Tests Conducted

Damaged GRC Gearbox #1

Lubrication System Diagram

CM System Configuration for Dynamometer Test


NREL 2.5-MW Dynamometer[6]

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Configuration • 2.5-MW induction motor • Three-stage epicyclical speed

reducer • Variable-frequency drive with full

regeneration capacity

Capabilities • Performance and reliability tests on wind turbine drivetrain

prototypes and commercial machines • Static, highly accelerated life and model-in-the-loop tests • Bed plate tilts up to 6° to mimic angle between the plane of the

blades and the turbine main shaft, as seen in the field • Rated output torque 1.4 MNm • Speed variation from 0 to 16.7 rpm rated torque, 16.7 to 30 rpm

rated power • Non-torque loads rated up to 880 kN for radial and 156 kN for thrust

NREL 2.5 MW Dynamometer/PIX08581


Test Articles

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Two gearboxes rated at 750 kW • One planet stage and two parallel stages • Redesign

Floating sun, cylindrical roller planet bearings, tapered roller bearings in parallel stages, pressurized lubrication, offline filtration and desiccant breather

• Up to 150 channels of measurements for loads, displacements, and temperature


Dynamometer Test Setup[5]

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Tests Conducted

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Dynamometer test of GRC gearbox #1: run-in Field test of GRC gearbox #1 Dynamometer test of GRC gearbox #2: run-in and non-

torque loading Retest of GRC gearbox #1 in the dynamometer



Damaged GRC Gearbox #1

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Annulus

Planet

Sun Gear

Gear Pinion

Pinion

Low-Speed Stage

High-Speed Stage

Intermediate-Speed Stage

Low-Speed Shaft

Intermediate-Speed Shaft

High-Speed Shaft

Planet Carrier

1. Completed dynamometer run-in test 2. Sent for field test: experienced two oil losses 3. Stopped field test 4. Retested in the dynamometer under controlled conditions

High-Speed Stage Gear[7]


Lubrication System Diagram

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A CM Configuration in Dynamometer Tests[7]

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As a research project, this set up is beyond the typical drivetrain CM configuration seen in the industry.


Results and Discussion

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Run-in Test Results • Oil Cleanliness Level

• Oil Debris Monitoring

• Oil Sample Analysis

Dynamometer Retest of the Damaged GRC Gearbox #1

• Stress Wave Analysis

• Vibration Analysis

• Oil Debris Monitoring

• Oil Condition Monitoring

Discussion


Run-in Results: Oil Cleanliness Level[8]

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A broad range of particles were found in the oil • Results: GRC

gearbox #1 • All three bins • Similar results: GRC

gearbox #2

Contamination level

• Increases when generator speed is ramped up • Decreases when generator is shut down and with the use of an operating

lubricant filtration system • Potentially useful for controlling the run-in of gearboxes


Run-in Results: Oil Debris Monitoring[9]

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Oil debris monitoring conducted throughout the GRC gearbox #2 run-in test period • K1 (left top), K2 (left

bottom) and K3 (right top) • Trends are similar though

particle counts vary


Run-in Results: Oil Sample Analysis[9]

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Results: GRC gearbox #2 • Particle counts: important to identify particle types

Analysis Results Reference Limits

• Element identification


Dynamometer Retest: Stress Wave Analysis[7]

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Dynamometer retest of GRC gearbox #1 (right) indicated abnormal gearbox behavior

Parallel stages sensor GRC gearbox #2

dynamometer test (left) indicated healthy gearbox behavior


Dynamometer Retest: Vibration Analysis[7]

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Intermediate speed shaft sensor

GRC gearbox #2 dynamometer test (left) indicated healthy gearbox behavior

Dynamometer retest of GRC gearbox #1 (right) indicated abnormal gearbox behavior • More side band frequencies • Elevated gear meshing

frequency amplitudes


Dynamometer Retest: Oil Debris Monitoring[7]

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Particle generation rates: • Damaged GRC gearbox #1: 70 particles/hour on 9/16 • Healthy GRC gearbox #2: 11 particles over a period of 4 hours


Dynamometer Retest: Oil Condition Monitoring

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Field test of GRC gearbox #1 (left): • Wild dynamics • Possible damage

Retest of GRC gearbox #1 (right): • Well controlled test

conditions • Possible damage


Discussion

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Oil cleanliness level measurement can potentially be used to control and monitor wind turbine gearbox run-in.

Oil debris monitoring, specifically particle counts, is effective for monitoring gearbox component damage, but is not effective for damage location.

If sensor mounting location is appropriate, similar trends in oil debris counts between the offline filter loop and the inline filter loop can be obtained.

When obtaining particle counts through oil sample analysis, attention should be given to identifying particle types.

Periodic oil sample analysis may help pinpoint failed component and root cause analysis.


Discussion (Cont.)

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Stress wave amplitude histogram appears effective for detecting gearbox abnormal health conditions.

Spectrum analysis of vibration signal (or stress waves) can, to a certain extent, pinpoint the location of damaged gearbox components.

Damaged gearbox releases particles at increased rates. Oil condition monitoring, specifically moisture, total

ferrous debris and oil quality: • Oil total ferrous debris appears indicative for gearbox

component damage • More data is required to understand oil moisture and quality

Electric signature-based technique did not reveal any gearbox damage in this study.


Concluding Remarks

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Challenges Future R&D Areas


Challenges[10]

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Justification of cost benefits for CM: each wind turbine has a relatively lower revenue stream than traditional power generation

Limited machine accessibility: makes retrofitting of CM systems or taking oil/grease samples difficult

Cost-effective and universal measurement strategy: sensor readings are affected by mounting locations and various drivetrain and gearbox configurations

Diagnostics: variable-speed and load conditions and very low rotor speeds challenge traditional diagnostic techniques developed for other applications

Data interpretation: requires expert assistance for data analysis and maintenance recommendations

Oil sample analysis: sample variations, different lubricant may require different sets of tests or procedures

Additional complexity for offshore: foundation, undersea transmission lines, saltwater and wave influences on turbine, and weather forecast.


Future R&D Areas[10]

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Determine cost-effective monitoring strategy Improve accuracy and reliability of diagnostic decisions,

including level of severity evaluation Automate data interpretation to deliver actionable

recommendations Develop reliable and accurate prognostic techniques Improve use of Supervisory Control and Data Acquisition

(SCADA) system data Research fleet-wide condition monitoring and asset

management Improve turbine operation, control strategy, and

component design through root cause analysis

Challenging yet Rewarding


References

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1. Global Wind Energy Council. Global Wind Report Annual Market Update 2010. http://www.gwec.net/index.php?id=180

2. R. Gao, R. Yan, S. Sheng, and L. Zhang, “Sensor Placement and Signal Processing for Bearing Condition Monitoring”, Condition-Based Monitoring and Control for Intelligent Manufacturing, Lihui Wang and Robert X. Gao (Eds.), Springer-Verlag, pp. 167-191, ISBN 1-84628-268-3, 2006.

3. Kewitsch, R. “Optimizing Life Cycle Costs (LCC) for Wind Turbines by Implementing Remote Condition Monitoring Service,” presented at the AWEA Project Performance and Reliability Workshop, January 12–13, 2011, San Diego, CA.

4. Wind Stats Newsletter, 2003–2009, Vol. 16, No. 1 to Vol. 22, No. 4, Haymarket Business Media, London, UK.

5. Dempsey, P. and Sheng, S. “Investigation of Data Fusion for Health Monitoring of Wind Turbine Drivetrain Components,” presented at the 2011 American Wind Energy Association WINDPOWER Conference, Anaheim, CA, USA, May 22-25, 2011.

6. National Renewable Energy Laboratory. 2.5-MW Dynamometer Testing Facility Fact Sheet. http://www.nrel.gov/docs/fy11osti/45649.pdf. Accessed July 27, 2011.

7. Sheng, S. “Investigation of Various Condition Monitoring Techniques Based on a Damaged Wind Turbine Gearbox,” 8th International Workshop on Structural Health Monitoring 2011 Proceedings, Stanford, CA, September 13-15, 2011.

8. Sheng, S.; Butterfield, S.; and Oyague, F. “Investigation of Various Wind Turbine Drivetrain Condition Monitoring Techniques,” 7th International Workshop on Structural Health Monitoring 2009 Proceedings, Stanford, CA, September 9-11, 2009.

9. Sheng, S. “Investigation of Oil Conditioning, Real-time Monitoring and Oil Sample Analysis for Wind Turbine Gearboxes,” presented at the 2011 AWEA Project Performance and Reliability Workshop, January 12–13, 2011, San Diego, CA.

10. Sheng, S. and Veers, P. “Wind Turbine Drivetrain Condition Monitoring – An Overview,” Machinery Failure Prevention Technology (MFPT) Society 2011 Conference Proceedings, Virginia Beach, VA, May 10-12, 2011.

http://www.gwec.net/index.php?id=180

http://www.nrel.gov/docs/fy11osti/45649.pdf


Thanks for Your Attention!

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Special thanks go to GRC CM partners: CC Jensen, Castrol, Eaton, GasTOPS, Kittiwake, Herguth Laboratories, Lubrizol, Macom, SKF, SKF Baker Instruments, and SwanTech!

NREL’s contributions to this presentation were funded by the Wind and Water Power Program, Office of Energy Efficiency and Renewable Energy of the U.S. Department of Energy under contract No. DE-AC02-05CH11231. The authors are solely responsible for any omissions or errors contained herein.