machinery prognostics and condition monitoring … · dr. karl reichard machinery ... • safety...

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Machinery Prognostics and

Condition Monitoring Technical

GroupDr. Karl Reichard

Machinery Prognostics & Condition Monitoring Technical Group

Applied Research Laboratory

Phone: (814) 863-7681

Email: [email protected]

Steve Conlon

Jeff Banks

Jason Hines

Joe Rose

Cliff Lissendon

Marty Trethewey

Mitch Lebold

Jason Hines

Steve Hambric

Joe Cusumano

Jeff Mayer

Bernie Tittman

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• Safety – early work in helicopter HUMS

• Maintenance – use HUMS to enable condition based maintenance (CBM)

• Manning – reduce manning through CBM and PHM

• Life Cycle Cost – reduce total life cycle cost through savings in maintenance, manning, and sustainment

• Logistics – extend savings through the enterprise by leveraging CBM and PHM across fleets of assets

• Asset Capability Management – manage asset health by matching mission requirements to capability

• Autonomous Operation– enable autonomous and automated response to changing external and internal operating conditions

Drivers for Health

Management


3

Embedded Diagnostics and Prognostics

Technology Development for Helicopter Power

Systems

Jeff Banks, Jeff Mayer, Todd Batzel, Matt Poese


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Test Setup for generator functionality

Drive rated for 11 HP @ 18,000 Rpm

3 phase VFD

AC motor

Electrical System

TestBed

200A load bank for

electrical loading


Starter /

Generator

5

Starter / Generator

Diagnostics

Focus has been on detecting sparking at brushes on the

surrogate starter/gen. Sparking increases wear rate of

brushes, which are a priority item for prognostics

heavy sparking moderate sparking light sparking

Test conditions:

• Imposed by rotation of brush assembly or removal of

interpole/compensation winding

• Field current measurements are performed under a

continuum of these operating conditions

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Starter / Generator

Diagnostics

Sparking Test Results

– Consistent increase in field current is observed as sparking

level increases

– True for sparking induced by brush assembly rotation and

removal of interpole / compensation winding

heavy sparkingmoderate sparkinglight sparking

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Power Inverter

Diagnostics

• Change in capacitance (tank phase) algorithm to allow identification to be done with loads within the tolerance of listed inverter specifications.

• Generated state space model for sensitivity calculations of the MOSFETs and current source inductor.

• Created algorithm to determine output tank parameters.

• Conducting long term inverter testing.

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Power Inverter

Diagnostics

T1

0

1

2

3

4R2

1mΩ C14.882uF

V115 V

Q16

IRF540

XSC1

A B C D

G

T

Q15

IRF540

U2A

4050BD_15V

C17

1uF

R36

100ΩR522kΩ

C2547nF

CR231N4148

L3

1nH

R8

100nΩ

L7

1mH

C4

1uF

R21

100ΩR2222kΩ

C547nFCR2

1N4148

U2B

4050BD_15V

V215 V

XFG1

U4A

LM339N

5

4

3

2

12

U4B

LM339N

7

6

3

1

12

R115kΩ

R95kΩ

V3

V4

Manual PWM Circuit

T3

1

01

234 5

D2DIODE_VIRTUAL

L127mH

MultiSim Simulation Test Circuit


-1.50E+02

-1.00E+02

-5.00E+01

0.00E+00

5.00E+01

1.00E+02

1.50E+02

0.0E+00 5.0E-04 1.0E-03 1.5E-03 2.0E-03 2.5E-03

-2.0E+00

0.0E+00

2.0E+00

4.0E+00

6.0E+00

8.0E+00

1.0E+01

1.2E+01

1.4E+01

1.6E+01

Output Q15 Gate Q16 Gate

-200

-150

-100

-50

0

50

100

150

200

-0.001 -0.0005 0 0.0005 0.001 0.0015 0.002 0.0025

-2

0

2

4

6

8

10

12

14

16

Output Q15 Gate Q16 Gate

Modeled Measured

Model-based

diagnostic and

prognostic approach

compares real-time

measurements to

model predictions

and historic data

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Health Monitoring of Wind

Turbines


Karl Reichard, Susan Stewart, Dennis McLaughlin

Brenton Forshey, Brian Wallace, Mark Turner, Nate Lasut, Scott Pflumm

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Wind Turbine

Monitoring

• Instrumented Penn State Center for

Sustainability‟s Southwest

Windpower Whisper 500, 3 kW,

turbine

• Sensors:

– 3 phase AC and converted DC power

– Tower and blade vibration

• Goals:

– Characterize wind-induced unsteady loads

– Monitor health of generator, blades,

batteries, and power conversion and

control electronics


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Blade Health

Monitoring


• Student team designed

and is fabricating new

blades for wind turbine

• New blades will contain

embedded accelerometers

to monitor blade vibration

and unsteady loads

• Wireless monitoring

system in hub will transmit

vibration information to

monitoring station at base

of turbine.• Future project – energy harvesting for

wireless monitoring system

12Machinery Prognostics & Condition Monitoring Technical Group

Wind Energy Testbed

• Laboratory-based electrical generator test bed permits study

of internal generator, drive train, and power electronic faults.

• Bearing testing planned for summer 2010

13Machinery Prognostics & Condition Monitoring Technical Group

Wind Energy Goals

• Monitor health and

status of individual

wind turbines

• Facilitate CBM by

predicting

equipment failures

and maintenance

requirements

• Optimize capacity

of wind farm by

aligning CBM with

forecasted weather

conditions

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Technology Evaluation and

Integration for Heavy Tactical

Vehicles

Applied Research Laboratory

The Pennsylvania State University

PI: Brian Murphy / PE: Mark Brought

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On-Vehicle Sensor

Integration for Monitoring

and Diagnostics

Applied to existing vehicle data sources• Integrate Vehicle Computer System (VCS)

• Develop and integrate common CBM graphical user interface

• Open data sources: J1939, J1708

• Proprietary data sources: ADM diagnostic messages, ADM operational parameters

Applied to new sensors- Engine oil condition analysis - Fuel level

- Engine oil level - Fuel filter condition

- Transmission oil level - Tire pressure monitoring

- Coolant sensor level - Brake wear monitoring

- Hydraulic reservoir oil level

Applied to power system components• Alternator: Voltage, Current, and Temperature

• Battery: V, I, T, State of Charge, and State of Health

• Ultracapacitor: V, I, T, and SOC

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Need for Primary Power

Management

• Reliable engine starting after long term storage

– AGM Battery loss on vehicles aboard Pre-Pro Ships (USNS Pomeroy)

– War Reserve, National Guard, etc. with long periods of inactivity

• Higher total power needed for high electrical demands (e.g.

A/C, C4ISR, CREW, IED countermeasures, lighting)

• Longer operation during „silent watch‟

• Reduced logistics burden

• Lower lifecycle costs

• Simplified maintenance and diagnostics

Battery Graveyard, Kuwait

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Primary Power Management

System (PPMS)

A common vehicle power & energy architecture across platforms

• Employs a split energy storage

system to optimize energy delivery

Uses a hydraulically-driven

alternator /generator for high

electrical power drive & accessory

loads

Uses ultracapacitor

for vehicle starting

Accommodates variety of

batteries to meet mission

requirements

Provisions

DC–AC, DC-DC

Power Sources

Integrates power

management &

control

Evaluated the utility

of a planetary gear

starters Accepts modular external

charging sources (e.g. BB-

2590, Solar, etc).

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Primary Power Management

System Built & Tested

Scalable across TWV‟s

Ultracapacitor and

controller for hybrid

starting system

PPMS

CTIS, ATC, ABS

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PPMS Key Findings

Findings:

• Hybrid starting system proved functional

• Works with wide range of batteries

• Ultracapacitors can restart vehicle many 1000‟s of times

• Hydraulic powered alternator proved functional

• Ultracapacitor recharge control system proven using BB

2590, can also use BB390 NiMH, etc.

Impact:

• Life cycle cost reduction, reliability, improved performance

in „silent watch‟ runtime, modularity, applicability across

family of TWV‟s

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Convoy Collision Warning

System

As-Built Prototype System for Test & Evaluation

•GPS and inertial sensors on each vehicle

•Wireless communication between vehicles

•Use of Netbook PC‟s

Approach

•Share precise separation distance

between vehicles

•Combine separation data and rate of

closure to determine warning

•Present audible and visual driver alert

System Testing• 2 and 3-vehicle testing conducted at

Penn State test track

• 3-vehicle convoy testing conducted

on PLS‟s at Yuma Proving Ground

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Convoy Collision

Warning System

Vehicle 2Vehicle 3

Vehicle 1

Immediate End of Test- all vehicles braked to a stop

Vehicle 2 “overran” Vehicle 1

Vehicle 3 stopped with headway between Vehicle 2

Takeaways:

• Red gives proper indicator of unsafe headway distance

• Need to tailor and adjust thresholds to optimize system

performance and driver effectiveness

Click Here for Movie

May have to exit out of

slide show to run it

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Automated Reporting

Information Displays

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Structural Health Monitoring


Cliff Lissendon

Engineering Science and Mechanics

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Application: Adhesively bonded joint integrity

Sponsor: NASA Aircraft Aging and Durability

Problem Statement: structural integrity relies on bonded joints, thus

characterization of joint strength is critical

Approach: ultrasonic guided waves interact with defects and depend

on elastic properties

Results: conversion of Lamb waves to interface waves

depends on dispersion curves and wave structures

Frequency (MHz)

An

gle

(D

eg

ree

)

Aluminum (2 mm) Dispersion curve - GMM and LLW

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

5

10

15

20

25

30

35

40

2525

Application: Composite laminate delamination detection

Sponsor: AFOSR Structural Mechanics

Problem Statement: low velocity impacts and other insults cause

invisible delaminations that reduce the compressive strength

Approach: phased array of piezoelectric transducers can focus and

steer energy that reflects off defects

Results: energy skewing has been overcome in

anisotropic laminates and segmented annular array

transducers developed

2626

Application: Fatigue crack prognostics in built-up structures

Sponsor: Ben Franklin Center of Excellence in SHM

Problem Statement: effective SHM relies on detecting, locating, and

sizing fatigue cracks in complex joint structures

Approach: piezoelectric sensor array to size fatigue crack at fastener holes

in built-up joints; probabilistic fatigue crack growth model predicts RUL

Results: fatigue crack located, probabilistic model

implemented using Monte Carlo simulation

Ni= 50 cycles

= 0.05

Cycles

Pr

acr = 0.015 m

2727

Application: Detect and size corrosion in well casing

Sponsor: DOE Gas Storage Technology Consortium

Problem Statement: corrosion in steel casing for gas storage wells

increases risk

Approach: design an ultrasonic tool for sizing corrosion and cracks

using both circumferential and longitudinal guided waves

Results: circumferential waves appear to be effective

Damage Reflection

Transmitted Wave

Reflected Wave

T R

T/R

Reflected Wave

Transmitted Wave

machinery prognostics and condition monitoring … · dr. karl reichard machinery ... • safety...

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