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Machinery Prognostics andMachinery Prognostics and Condition Monitoring Technical

GroupGroupDr. Karl Reichard

Head, Complex Systems Monitoring and Automation Dept.Applied Research Laboratory

Phone: (814) 863-7681 Email: [email protected]

1Machinery Prognostics & Condition Monitoring Technical Group

Drivers for Health Management

• 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 savingsLife 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 assetse e ag g C a d ac oss eets o assets• Asset Capability Management – manage asset health by

matching mission requirements to capability• Autonomous Operation– enable autonomous andAutonomous Operation enable autonomous and

automated response to changing external and internal operating conditions


Embedded Diagnostics and Prognostics TechnologPrognostics Technology Development for Helicopter Power Systems ffSystems Jeff Banks


Technical Approach

• For more accurate/reliable diagnostics, need to test components under realistic conditions• Developing TestBed to characterize starter & battery performance (engine start) and generator performance (electrical loading)

C tl h li it d l tf d t• Currently have very limited platform data• Need to conduct on-platform testing & data collection to facilitate TestBed designg


Electrical System TestBed

3 phase VFD AC motor • PMA fixtures currently

being fabricated• Also building 200A load bank for electricalload bank for electrical loading

Test Setup for generator functionalityDrive rated for 11 HP @ 18,000 Rpm


Electrical System TestBed

• Need to properly load starter, p p y ,but not overstress PMA shaft

• Investigating use of magnetic ti l b k ( l d iparticle break (already in-

house)• Need gear ratios and trueNeed gear ratios and true

turbine speed• At what speed does turbine

li h ( di )?light (starter disengage)?

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Gear Train For Start ModeMachinery Prognostics & Condition Monitoring Technical Group

Battery Diagnostics & Prognosticsg

• Initial results comparing PSU-ARL EIS hardware (blue) to Solartron (red)(blue) to Solartron (red)

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6x 10-3

EIS

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Circuit Model

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0.025 0.03 0.035 0.04 0.045 0.05 0.055-2

real(Z)Machinery Prognostics & Condition Monitoring Technical Group

Battery Diagnostics & Prognostics

PSU-ARLPSU-ARL Battery Test StationStation- used to test battery

UPS performance

• 4 independent electronic load banks• 4 independent power supplies

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• Equipment control, data logging with LabVIEW software• Freezer and high temperature chamber

Machinery Prognostics & Condition Monitoring Technical Group

Power Inverter Diagnostics

• Creating MultiSIM circuit representation of inverter• Match behavior to actual inverterMatch behavior to actual inverter

• Use to perform fault testing

Ch t i b li f i l d b k• Characterize baseline performance using load bank• HALT or seeded faults will be used for future testing

KGS Electronics

Model SE25



• 3 independent load cells can be configured as– Delta– Wye– Single phase

0 240V• 0 to 240V• 128 resistance steps per cell

– 120V• 20mA increments• 1.28A maximum

– 240V• 40mA increments• 40mA increments• 2.56A maximum



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MultiSim Simulation Test CircuitMachinery Prognostics & Condition Monitoring Technical Group


1.50E+02 1.6E+01 200 16

Simulation Actual

0 00E+00

5.00E+01

1.00E+02

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1.0E+01

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• Still tweaking simulation to better match results of actual circuit

• Better quantify circuit parameters (mainly magnetics)


PM Heavy Brigade Combat Team Vehicle Health Management System: Thermal Analysis for Track andManagement System: Thermal Analysis for Track and

Suspension Diagnostics

Jeffrey Banks, Mark Brought and CW04 Wittcop (U.S.M.C.)ARL Penn State (814) 863-3859

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(814) 863 [email protected]


Objective

• Track and suspension systems presents a challenge f th i l t ti f b dd d di tifor the implementation of embedded diagnostic technology, though potential solutions are being evaluatedevaluated

• ARL Penn State is evaluating the utility and effectiveness of using thermography technology as a potential at-platform technology for detecting track & suspension system faults.

• Thermography technology is a widely used and• Thermography technology is a widely used and effective CBM technology in industry for several decades.


Track & Suspension System Failure Modes

• It has been determined that there are three dominant and critical failure modes:

– HUB bearing failure from lost of lubrication from cracked hub cover

– Road wheel rubber failure

– Loose bolts causes the road wheel bolt holes to enlarge (wallow out)

• Our research objective is to determine if these failure modes can be detected well before failure occurs using thermography.– We need to gather baseline data to quantify the temperature variance g q y p

between track & suspension system components during normal operation.

– We need to gather failure data to evaluate the difference in temperature

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We need to gather failure data to evaluate the difference in temperature during failure from the normal temperature range during operation to evaluate detectability of the failure modes.


Temperature Analysis Approach

• We will be using a standardQualitative TemperatureQualitative Temperature Analysis technique:– A comparison of the thermal

signal of a subject to that of an g jidentical or similar subject at the same or similar operating condition.

Th h lth t i b d• The health assessment is based on the variation in temperature between the compared subjects.– Accurate temperature level is not

h tnecessary when measurements are taken under the same conditions.

Can use a standard baseline

• Less time consuming to make measurement because camera setup is simpler.

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– Can use a standard baseline measurement as the reference ‘healthy’ condition.

• Not an effective technique for all applications.


Initial Assessment: NTC Data

• Currently collecting baseline data for evaluating tracked vehicle suspension systems.– Typical example of a M1A2 Abrams tank suspension

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– Typical example of a M1A2 Abrams tank suspension system.


NTC ThermographyExample: Abrams

• After a seven hour mission a thermographyAfter a seven hour mission, a thermographycamera was used to inspect three vehicles.

• Although not conclusive this is an example of

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Although not conclusive this is an example of possible suspect road wheels.


Baseline Temperature Data: Single Vehicle

• We have started the technology evaluation by characterizing the variance in temperature between the road wheels for each side of the ehiclethe vehicle.


Baseline Temperature Data: Multiple Vehicles

• We have compiled average temperatures for each road wheel for each side of• We have compiled average temperatures for each road wheel for each side of the vehicle from 10 vehicles that ran the same speed, distance and test course.

• This data helps to establish the characteristic ‘normal’ operation temperature range

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range.

• This data is important for determining detectability. Machinery Prognostics & Condition Monitoring Technical Group

Why Thermography and Acoustics?

• False alarms are still a limiting factor for acceptance of automated diagnostic and prognostic systems

• Thermography and Acoustics are noncommensurate sensor types - noncommensurate sensor data fusion is a good technique for reducing false alarms because particularly oftechnique for reducing false alarms because, particularly of the fault causes a response in both indicators, but noise sources affect the two measurements differently (ex. Road conditions and brake faults)conditions and brake faults)

• Goal is to combine embedded, on-platform health monitoring with simple, off-platform inspection to reduce false alarms and no evidence of fault found

• Thermography can be replaced with appropriate thermal sensors

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sensors


Mission Planning and Assessment

Jeff BanksKarl Reichard


Concept

• Show the utility of merging vehicle location information with VHMS fuel data for conducting vehicle/unit fuel need planning and vehicle/unit fuel usage assessmentvehicle/unit fuel usage assessment.

• Use as an off-platform PC based information portal for fuel logistic planning.• The tool was developed for the Marine Corps AL program but it isThe tool was developed for the Marine Corps AL program but it is

applicable to the Army VHMS program. • VHMS fuel data would potentially be provided from LIA or LOGSA

to populate this portal. • Demonstrate how more accurate fuel use projections can be

developed based on mission data and how the prediction of fuel usage can be updated based on fuel level and mileage data from the vehicle VHMS systemvehicle VHMS system.• We use a U.S.M.C MTVR vehicle at our facility in State College, PA

for this presentation.• We use COBRA and NTC GPS data for the active demonstration

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• We use COBRA and NTC GPS data for the active demonstration.


Mission Planning Tool

• The user creates a mission plan using Google d i i di tidriving directions or manually.

• This fuel usage planning toolplanning tool allows the user to input mission parameters that impact fuel usage.usage.

• The model uses latitude and longitude, elevation andelevation and temperature look up tables and calculated gradient to estimate fuel

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estimate fuel use over the mission plan.


Vehicle Mission Tracking: Fuel and Health

• The top portion of theportion of the display allows the user to conduct mission tracking and gassessment for individual vehicles or units.

• The bottom portion of the display allows the user to quicklyquickly assess vehicle fuel level and health status.


Fuel Mission Tracking and Assessment

• The top portion of the displayof the display shows the projected fuel usage rate as a function of miles driven based on the model calculations and missionmission parameters.

• The bottom portion of theportion of the display shows the projected mission plan on the map.

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p


Fuel Mission Tracking and Assessment

• The top portion of the display showsthe display shows the actual fuel usage rate based on fuel data from the vehicle EDC sent through

t llitsatellite communications to off-platform servers.

• The bottom portion• The bottom portion of the display shows vehicle tracking, status and warnings of updated fuel level

j ti th tprojections that indicate that the vehicle needs refueling before the end of the mission plan.

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p


Application to Diagnostics and Prognostics

PlatformPlatform Mission

Platform Database

Platform DatabaseMission

Planning Tool

Databases

Tool

Mission demandsDegraders Current

HealthMission demands and loads

•Probability

On-platform PHM

•Severity

•What to monitor

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•What to repair•Vehicle availability


Focus Areas for Machinery Condition Monitoring

• Sense and Respond and Autonomic pLogistics

• Unmanned SystemsUnmanned Systems• Prognostics and Advanced Diagnostics

D t F i f R d i N E id f• Data Fusion for Reducing No Evidence of Fault

• Electronics• Structural Health Monitoring

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g• Integrated System DesignMachinery Prognostics & Condition Monitoring Technical Group

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