The presentation provides an overview of Condition Based Maintenance research performed in the NASA Glenn Tribology and Mechanical Components Branch in support of the Subsonic Rotary Wing Project

Dempsey, Paula J.

NASA Technical Reports Server

Condition Based Maintenance 
 
 
Summary:   
The presentation provides an overview of Condition Based Maintenance 
research performed in the NASA Glenn Tribology and Mechanical 
Components Branch in support of the Subsonic Rotary Wing Project. 
https://ntrs.nasa.gov/search.jsp?R=20110011337 2019-08-30T15:26:46+00:00Z
1National Aeronautics and Space Administration
www.nasa.gov
Fundamental Aeronautics Program
Dr. Paula Dempsey
Tribology & Mechanical Components Branch
NASA Glenn
Subsonic Rotary Wing Project
CBM
2011 Technical Conference
March 15-17, 2011
Cleveland, OH
What is CBM?
Condition Based Maintenance: 
Application & integration of processes, technologies & 
knowledge via a systems approach to improve aircraft 
reliability and maintenance effectiveness*
» Reduce maintenance tasks
» Increase aircraft availability 
» Improve flight safety 
» Reduce costs
*US Army ADS-79 HNDBK
2
CBM Functions
Propulsion System Health
• Health monitoring of dynamic mechanical components 
• Monitored by vibration signature analysis methods (condition indicators-
CI) and oil condition
Structural Health
• Fatigue life management/component lifing based on actual usage & 
regime recognition
Exceedance Monitoring
• Aircraft operational/parametric data (torque, speed, temperature)
Engine Health
• Power assurance check/Power Management
Rotor Smoothing
• Automated track & balance of rotors to decrease vibrations
Fleet Maintenance
• Logging maintenance actions/CBM data 3
Propulsion System Health
– Improved detection techniques
– Improved diagnostic algorithms
• Multi-sensor data fusion
• Performance metrics
• Damage magnitude assessment
– Validated methods – rotorcraft field verification 
• Test methods representative of fielded faults
– Future prognostic algorithms
• Damage life prediction models – predict remaining useful life
Structural Health & Exceedance Monitoring
– Correlate aircraft operational parameters to component life.  
Research enabled through Partnerships with the FAA and US Army
– FAA funded Space Act Agreements
– Access to > 2000 Army HUMS equipped helicopters
SRW CBM Focus - Propulsion
Gear Fault Detection Effectiveness 
Objective:
•Evaluate gear tooth pitting fatigue     
fault detection effectiveness
•Evaluate repeatability of gear tooth 
fault detection methods
•Evaluate CI threshold values
Approach:
•Test gears: face gears with tapered 
involute pinions
•Vibration and oil debris monitoring  
during gear endurance testing
• Evaluate three common vibration 
CIs (RMS, FM4, NA4)
Propulsion System Health
Data point
0 10000 20000 30000
NA4 (g's) - Healthy
0
3
6
9
12
Data point
0 1000 2000 3000 4000
NA4 (g's) - Faulty
0
10
20
30
40
50
NA4
0 20 40 60 80
Probability density function
0.0
0.1
0.2
0.3
0.4
False alarm rate
0.0 0.2 0.4 0.6 0.8 1.0
Hit rate
0.0
0.2
0.4
0.6
0.8
1.0
Healthy
Faulty
NA4=35 4620
40
CI:  NA4,  Macro-Pitting, Single/Few Teeth
Propulsion System Health
Gear Fault Detection Effectiveness 
Planetary Fault Detection
Objective:
Demonstrate diagnostics to detect gear and bearing planetary system faults 
in main-rotor gearbox
Approach
Develop algorithms from seeded fault tests on the OH-58 main-rotor 
transmission (AATD/Bell OSST)
0  45 90 135180225270315360 45 90 135180225270315360 45 90 135180225270315360
-5
0
5
a) Hunting tooth average of raw data.
A
c
c
e
l
e
r
a
t
i
o
n
 
(
V
)
34 35 1 2 3 
-2
0
2
b) Windowed data, 
planet 1 carrier 
cycle 1.
A
c
c
e
l
e
r
a
t
i
o
n
 
(
V
)
Tooth number
28 29 30 31 32
-2
0
2
Tooth number
22 23 24 25 26
-2
0
2
Tooth number
1 2 3 4 5 6 7 8 9 1011121314151617181920212223242526272829303132333435 1 
-2
0
2
Planet gear tooth number
A
c
c
e
l
e
r
a
t
i
o
n
 
(
V
)
e) Completed planet 1 tooth vector.
Planet 1 first pass Planet 1 second pass Planet 1 third pass
c) Windowed data, 
planet 1 carrier 
cycle 2.
d) Windowed data, 
planet 1 carrier 
cycle 3.
Carrier rotation, deg
Propulsion System Health
Ac
c
e
l
e
r
a
t
i
o
n
,
 
g
'
s
-15
-10
-5
0
5
10
15
A
c
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l
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r
a
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i
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n
,
 
g
'
s
-15
-10
-5
0
5
10
15
A
c
c
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l
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r
a
t
i
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n
,
 
g
'
s
-10
-5
0
5
10
Planet gear tooth number
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35
A
c
c
e
l
e
r
a
t
i
o
n
,
 
g
'
s
-10
-5
0
5
10
Accelerometer number
A1 A2 A3 A4 A5 A6 A7 A8
M
8
A
0
500
1000
1500
2000
15000
20000 Healthy
Faulty
Fault
Propulsion System Health
Planetary Fault Detection
9
9
Time Domain
Frequency Domain
time steps
undamaged
damaged
S
u
n
 
G
e
a
r
 
D
i
s
p
l
a
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m
e
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t
 
Objective:
Develop analysis method to simulate 
dynamic response of gear or bearing 
surfaces with damage
Approach:
•Defect geometries defined by actual 
measurements
•Forces between components calculated 
via contact mechanics
•Deformations and vibration responses 
calculated via finite element
Propulsion System Health
10
Objective:
• Demonstrate (CI) responds to 
failure progression  & correlates 
to remaining useful life 
Approach:
• UH60 tail gearbox output shaft 
thrust bearings 
• Removed from helicopters 
installed in test stand
• Periodic inspections to 
measure spall growth
• CI data mapped to the damage 
state did not perform well for 
magnitude assessment
• Oil debris sensor monitored 
debris generation & indicated 
progression & remaining life.
Propulsion System Health
FAA Space Act Agreement 
Validation & Demonstration of HUMS for Maintenance Credits,
modified inspection & removal criteria,
via FAA  AC-29-2C, Section MG-15
Objectives:
• Develop CI validation methods in the lab that represent fielded faults
• Identify limitations of seeded fault data sets. 
• Case Study: Component with naturally occurring faults in the field and 
test stand.
9 Spiral bevel gears in the Apache nose gearbox (NGB)
9 Spiral bevel gears tested in the Spiral Bevel Gear Fatigue Test Rig
Approach
• Rig gears designed/tested with loads/speed scaled to NGB
• Field units studied for failure modes & operational environment 
• Field/Rig data studied for CI performance
• Usage data studied to determine if failure can be correlated to usage 
Collaborative Team Effort:  FAA, US Army, NASA, Boeing
sPinion Magnetic 
Tach
Oil Debris Sensor
MSPU 
IAC Model 1087
MDSS
Torque Meter
Chip 
Detector
Gear Optical Tach
s
Spiral Bevel Gear Fatigue Rig
FAA Space Act Agreement 
13
FAA Space Act Agreement 
Assess CI performance from field & lab
0
25
50
75
100
125
150
1 10 100 1000 10000 100000
T
o
r
q
u
e
 
(
%
)
Hours
Correlate usage to failures
SRW Phase II SBIR
14
OH-58 main rotor 
transmission
NASA GRC 500-hp 
transmission test facility
Ridgetop
wireless 
sensors
Embedded Data Acquisition Tools  
for Rotorcraft HUMS (Ridgetop) 
Objective:
Develop MEMS wireless sensor for 
fault detection in rotorcraft 
transmission applications  
Approach:
• Develop MEMS vibration-monitoring  
accelerometer, microcontroller 
conditioner, wireless transmitter, and 
receiving unit for data collection.
• Mount directly on helicopter 
transmission component of interest to 
measure abnormalities and faults.  
SRW Phase I SBIR
15
Optical oil-debris sensor for 
rotorcraft health monitoring 
(Translume)
Objective:
Develop an oil debris sensor to 
monitor rotorcraft power train oil. 
Approach:
• Develop sensor to simultaneously 
detect both metallic and non-
metallic debris 
• Optimize sensor to detect, count 
and size particles
• Conduct a feasibility demonstration 
on a laboratory scale
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CBM (Condition Based Maintenance)

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