Jason S. Kiddy

Aither Engineering, Inc., Lanham, Maryland

Paul D. Samuel

Daedalus Flight Systems, LLC, Gaithersburg, Maryland

David G. Lewicki

Glenn Research Center, Cleveland, Ohio

Kelsen E. LaBerge

U.S. Army Research Laboratory, Glenn Research Center, Cleveland, Ohio

Ryan T. Ehinger

Bell Helicopter Textron, Inc., Hurst, Texas

Jason Fetty

U.S. Army Aviation Applied Technology Directorate, Fort Eustis, Virginia

Fiber Optic Strain Sensor for 

Planetary Gear Diagnostics

NASA/TM—2011-217123

November 2011

AHS 2011–000154
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Jason S. Kiddy

Aither Engineering, Inc., Lanham, Maryland

Paul D. Samuel

Daedalus Flight Systems, LLC, Gaithersburg, Maryland

David G. Lewicki

Glenn Research Center, Cleveland, Ohio

Kelsen E. LaBerge

U.S. Army Research Laboratory, Glenn Research Center, Cleveland, Ohio

Ryan T. Ehinger

Bell Helicopter Textron, Inc., Hurst, Texas

Jason Fetty

U.S. Army Aviation Applied Technology Directorate, Fort Eustis, Virginia

Fiber Optic Strain Sensor for 

Planetary Gear Diagnostics

NASA/TM—2011-217123

November 2011

AHS 2011–000154

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135

Prepared for the

67th Annual Forum and Technology Display (Forum 67)

sponsored by the American Helicopter Society (AHS)

Virginia Beach, Virginia, May 3–5, 2011
Acknowledgments

This research was partially funded by the Government under Agreement No. W911W6-07-2-0003. 

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Available electronically at http://www.sti.nasa.gov

Level of Review: This material has been technically reviewed by technical management. 
NASA/TM—2011-217123 1

Fiber Optic Strain Sensor for Planetary Gear Diagnostics

Jason S. Kiddy

Aither Engineering, Inc.

Lanham, Maryland 20706

Paul D. Samuel

Daedalus Flight Systems, LLC

Gaithersburg, Maryland 20877

David G. Lewicki

National Aeronautics and Space Administration

Glenn Research Center

Cleveland, Ohio 44135

Kelsen E. LaBerge

U.S. Army Research Laboratory

Glenn Research Center

Cleveland, Ohio 44135

Ryan T. Ehinger

Bell Helicopter Textron Inc.

Hurst, Texas 76053

Jason Fetty

U.S. Army Aviation Applied Technology Directorate

Fort Eustis, Virginia 23604

Abstract

This paper presents a new sensing approach for helicopter 

damage detection in the planetary stage of a helicopter transmission based on a fiber optic strain sensor array. Complete 

helicopter transmission damage detection has proven itself a 

difficult task due to the complex geometry of the planetary 

reduction stage. The crowded and complex nature of the 

gearbox interior does not allow for attachment of sensors 

within the rotating frame. Hence, traditional vibration-based 

diagnostics are instead based on measurements from externally mounted sensors, typically accelerometers, fixed to the 

gearbox exterior. However, this type of sensor is susceptible to 

a number of external disturbances that can corrupt the data, 

leading to false positives or missed detection of potentially 

catastrophic faults. Fiber optic strain sensors represent an 

appealing alternative to the accelerometer. Their small size 

and multiplexibility allows for potentially greater sensing 

resolution and accuracy, as well as redundancy, when employed as an array of sensors. The work presented in this 

paper is focused on the detection of gear damage in the planetary stage of a helicopter transmission using a fiber optic strain 

sensor band. The sensor band includes an array of 13 strain 

sensors, and is mounted on the ring gear of a Bell Helicopter 

OH-58C transmission. Data collected from the sensor array is 

compared to accelerometer data, and the damage detection 

results are presented.

Introduction

In recent years, much research has been devoted to the development of Health and Usage Monitoring Systems (HUMs) 

for rotorcraft. The promise of HUMS is the ability to provide 

accurate information regarding the condition of various flight 

critical components, enabling scheduled maintenance intervals 

to be increased and minimize the number of parts decommissioned before the end of their useful life, and thus reducing 

operating costs associated with civilian and military helicopters. In addition, an increase in helicopter safety and reliability 

could be realized.

The transmission is one of the significant flight critical 

components within the helicopter, and a large portion of 

helicopter transmission HUMS research has been focused on 

the use of vibration-based damage detection techniques. These 

techniques are applied to vibration signals collected from 

vibration transducers, typically accelerometers. Helicopters 

use a planetary gearbox as the final stage of the transmission.

The detection of damage within helicopter transmissions has 

proven to be a particularly difficult task. The crowded and 

complex nature of the planetary gearbox interior does not 

allow for robust attachment of sensors within the rotating 

frame. Hence, traditional vibration-based diagnostics are 

instead based on measurements from externally-mounted 

accelerometers fixed to the gearbox exterior. Advanced 

processing of this global vibration data provided by the 
NASA/TM—2011-217123 2

accelerometers can enhance the appearance of signal anomalies that indicate the presence of damage within the gearbox. 

Much effort has been focused on the use of accelerometer 

vibration data for helicopter transmission damage detection

(Refs. 1 to 3). However, this type of sensor is susceptible to a 

number of external disturbances that can corrupt the data, 

leading to false positives or missed detection of potentially 

catastrophic faults.

Fiber optic strain sensors represent an appealing alternative 

to the accelerometer due to their resistance to electromagnetic 

interference and other signal corrupting influences. Their 

small size and multiplexibility allows for potentially greater 

sensing resolution and accuracy, as well as redundancy, when 

employed as an array of sensors.

Researchers have established the capability of fiber optic 

sensors for structural health and usage monitoring systems

(Ref. 4), but their use with dynamic systems has been limited.

The use of fiber optic strain sensors to detect damage in the 

internal components of a helicopter transmission is an emerging area of research and thus few results have been published 

to date.

The feasibility of such a system to detect planetary gearbox 

damage has been only recently demonstrated (Ref. 5), and 

signal processing techniques that enhance the appearance of 

such damage are in their infancy (Refs. 6 and 7). 

The work presented in this paper is focused on the detection 

of gear damage in the planetary stage of a helicopter transmission using a fiber optic strain sensor band. The sensor band 

includes an array of 13 strain sensors, and is mounted on the 

ring gear of a Bell Helicopter OH-58C transmission. Data 

collected from the sensor array is compared to accelerometer 

data, and the damage detection results are presented.

NASA Glenn OH-58 Test Stand

The tests were performed in the NASA Glenn Research 

Center 500-hp helicopter transmission test facility using an 

OH-58C helicopter main-rotor transmission, as shown in 

Figure 1. The test stand operates on the closed-loop or torqueregenerative principle. Mechanical power recirculates through 

a closed loop of gears and shafting, part of which is the test 

transmission. A 200-hp variable-speed direct-current (DC) 

motor powers the test stand and controls the speed. A 15-hp 

DC motor provides the torque in the closed loop. A mast shaft 

loading system in the test stand simulates rotor loads imposed 

on the OH-58C transmission output mast shaft. The OH-58C 

transmission output mast shaft connects to a loading yoke. 

Two vertical load cylinders connected to the yoke produce lift 

loads. A single horizontal load cylinder connected to the yoke 

produces a bending load (Ref. 8).

Fiber Optic Strain Sensors

Fiber Bragg Gratings (FBGs) have become an integral part 

of the telecommunications hardware, used in applications such 

as add/drop filters, fiber lasers, and data multiplexing (Ref. 9). 

Figure 1.—NASA Glenn 500 Horsepower Helicopter Transmission Test Facility.

Figure 2.—Schematic of a fiber Bragg grating.

As shown in Figure 2, the FBG sensor is fabricated by altering 

the refractive index, n, of the core of an optical fiber in a periodic fashion, creating a Bragg grating that reflects a specific 

wavelength of light, referred to as the Bragg wavelength.

The period of the change is referred to as the grating pitch. 

Both the effective refractive index of the core and the grating 

pitch vary with changes in strain and temperature, so that the 

Bragg wavelength shifts to higher or lower wavelengths in 

response to applied thermal-mechanical fields. For most 

applications including the transmission monitoring system, the 

shift in the Bragg wavelength is considered a linear function 

of the thermal-mechanical load. In addition, for the present 

application, the thermal response of the system is much slower 

than the expected mechanical response and thus can be easily 

filtered out. Hence, a strain-based vibration signal can be 

measured by recording the changes in the wavelength of the 

light reflected from a given FBG as shown in the following 

equation. In this equation, λB is the Bragg wavelength, Pe is a 

constant scaling term, and εz is the longitudinal strain in the 

direction of the fiber.

 

200-hp dc motor

15-hp

dc motor

Magnetic

particle

clutch

Torque increaser

gearbox

Differential gearbox

Closing-end gearbox

Bevel gearbox

Mast load

cylinders

Test transmission

Slip rings

Speed decreaser

gearbox
NASA/TM—2011-217123 3

e z

B

B = P ε

λ

Δλ

The optical response of an FBG sensor is wavelength encoded allowing many FBG sensors to be serially multiplexed 

via wavelength division multiplexing techniques. Each FBG 

reflects a different wavelength, and sufficient space is provided so that strain does not cause the wavelength of the light

reflected from two separate sensors to overlap when strained.

The space required as well as the wavelength range of the 

interrogator box limit the number of sensors. Many commercially available interrogation systems have come to market 

making these types of sensors and systems readily available to

the end user.

FBG Strain Sensor Array Band

For this research, an array of 13 FBG strain sensors was 

mounted on a tension band clamp as shown in Figure 3.

Previous testing has shown that good strain transfer can be 

obtained with the clamp mounted to the outside of a ring gear

(Refs. 6 and 7). The advantage of the band clamp is that it 

relatively easy to install and remove as necessary.

The OH-58C ring gear is secured to the transmission housing with the use of splined teeth along the outside edge of the 

ring gear that mate with corresponding splines on the transmission housing. Therefore, modifications to both the ring 

gear and transmission housing were needed.

The modifications to the ring gear itself were two-fold. 

First, a section of the spline teeth along the entire circumference of the gear was removed to allow for the sensor band to 

be strapped to the outside. And second, two smaller portions 

had the spline teeth completely removed to allow for the 

optical fiber to egress off of the ring gear and onto the top of 

the transmission case where it exited from the transmission. 

The ring gear was modified as shown in Figure 4.

There were three main modifications to the transmission 

housing that were required. The first was to machine a section 

near the mounting bracket to allow for the band clamp tensioning mechanism. The second was to machine away some of 

the spline teeth for the fiber to egress off of the band and then 

to the top of the housing, and the third was to add a groove in 

the oil port to allow the fiber to exit the transmission. Additional modifications were necessary to secure the optical cable 

to the top of the housing; those were made in-house following 

the more intensive machining processes. The modified housing is shown in Figure 5.

Fiber Optic Strain Sensor and Corresponding Accelerometer Locations

After assessing several possible accelerometer and fiber 

optic sensor locations, the final placement was selected. The 

final fiber optic sensor and accelerometer locations are listed 

in Table I, and shown in Figure 6. Note that in Sensor 

Figure 3.—Band clamp schematic.

Figure 4.—Modified OH-58C ring gear.

Figure 5.—Transmission housing modifications.

Region 1, the two secondary fiber optic sensors were designed 

to be half the length of standard FBG sensors, about 5 mm 

versus 1cm for standard FBGs. Although the optical properties 

suffer slightly, the shorter sensors were used to determine if a 

strain gradient across the sensor affected their performance.

Although not discussed in detail in this paper, the difference

was minimal and standard FBGs performed adequately. For 

the set of fiber optic sensor locations, stud-mounted accelerometers were aligned with the primary fiber sensors in regions 

2 and 3 at teeth 9 and 71, respectively. In addition, a bracketmounted accelerometer was mounted on the bolt in region 1, 

which is near tooth 40.
NASA/TM—2011-217123 4

TABLE I.—FINAL FIBER OPTIC SENSOR LOCATIONS (0.5 L INDICATES 5 mm SENSOR)

Sensor Ring tooth referenced location: 

Sensor Region 1 

(Planet Tooth 1)

Ring tooth referenced location: 

Sensor Region 2 

(Planet Tooth 34)

Ring tooth referenced location:

Sensor Region 3 

(Planet Tooth 32)

Primary fiber optic sensor 40 9 71

Secondary fiber optic sensors 39 (0.5 L), 41 (0.5 L) 7, 8, 10, 11 70, 70.5, 71.5, 72

Accelerometer 40 

(bracket-mounted on nearest bolt)

9 

(stud-mounted)

71 

(stud-mounted)

Figure 6.—Final FO sensor and accelerometer locations.

The optical fiber selected was polyimide coated. A 

polyimide coating, as opposed to the more standard acrylate 

coating, gives higher temperature performance at the expense 

of being a bit more difficult to handle due to its smaller size 

and higher susceptibility to optical bend losses. The optical 

fiber was bonded to the clamp using conventional strain gauge 

epoxy, Vishay Measurements Group AE-10. The fiber was 

bonded along the entire length of the band clamp with the 

exception of a region within a couple of inches from each of 

the tensioning brackets. In those regions, small-diameter 

fiberglass jacketing made by Varflex, Inc. was slid over the 

fiber and also bonded in place. The Varflex helps protect the 

egress location. Additional thicker cabling was then added to 

further protect the fiber as it runs along the top cover and out 

of the transmission. Upon installation, portions of the cable at 

the band clamp tensioning bracking and exiting the oil fill port 

were coated with silicon rubber to secure the optical fiber 

cabling. The band sensor cable is approximately 1 m long at 

which point it terminates in a standard telecommunications 

FC/PC connector. From this point a standard fiber optic 

patchcord connects the sensor to the instrumentation in the 

control room.

Experimental Procedure

The major goal of the project was to study data collected at 

the NASA Glenn Research Center OH-58 transmission test rig 

facility from the fiber optic ring gear sensor array. First, the 

healthy data was evaluated to determine the fundamental 

characteristics of the OH-58C transmission strain signal 

waveform. Second, damage data was evaluated to determine 

how various types of damage are manifested in the OH-58C

1

41 (0.5L)

40

39 (0.5L)

70, 70.5

71

71.5, 72

Region 2

Region 1

Region 3

11

10

9

8

7

Region 3 

Accelerometer 

Stud-Mounted 

at tooth 71

Region 2 

Accelerometer 

Stud-Mounted 

at tooth 9

Region 1 

Accelerometer 

Bracket-Mounted at 

bolt near tooth 40

1

41 (0.5L)

40

39 (0.5L)

70, 70.5

71

71.5, 72

Region 2

Region 1

Region 3

11

10

9

8

7

Region 3 

Accelerometer 

Stud-Mounted 

at tooth 71

Region 2 

Accelerometer 

Stud-Mounted 

at tooth 9

Region 1 

Accelerometer 

Bracket-Mounted at 

bolt near tooth 40
NASA/TM—2011-217123 5

strain signal. An initial evaluation was used to determine the 

effectiveness of existing damage detection algorithms and to 

select a damage detection approach. After determination of the 

damage detection approach, the damage data was evaluated to 

ascertain how each type of damage is manifested in the signal, 

and how well each type of damage could be detected using the 

selected approach. Third, the effect of torque variation and 

mast loading on the strain signal waveform as well as on the 

damage-detection performance was investigated.

The damaged test cases that were considered are as follows:

• 1-1: Baseline test

• 1-2A: Planet pinion root crack, 25 percent depth, sun-side 

crack opening

• 1-2B: Planet Pinion root crack, 25 percent depth, ring-side 

crack opening

• 1-3A: Planet pinion root crack, 50 percent depth, sun-side 

crack opening

• 1-3B: Planet pinion root crack, 50 percent depth, ring-side 

crack opening

• 1-4A: Planetary pinion tooth spalled at the pitch line, sunside

• 1-4B: Planetary pinion tooth spalled at the pitch line, ringside

• 1-5: Sun gear root crack, 25 percent depth 

• 1-6: Sun gear tooth spalled at the pitch line 

• 1-7: Ring gear root crack, 25 percent depth 

• 1-8: Ring gear root crack, 50 percent depth

• 1-9: Planet bearing outer race pitting 

• 1-10: Planet bearing inner race pitting 

The fiber optic instrumentation used during this program, 

Micron Optics sm130 interrogator, had a maximum sampling 

rate of 1,000 Hz. Standard operating speed of the input shaft to 

the transmission is 6,180 rpm. However, at that speed the fiber 

optic instrumentation would be unable to resolve individual 

tooth meshes. Therefore, the transmission was operated at 

2,060 rpm for the fiber optic testing. Data collection was 

performed for each test condition; damage case, torque level, 

mast loading on/off, for a total of 30 hunting tooth cycles. The 

hunting tooth cycle is defined as the period in which the 

position of all planetary gear teeth repeats, and is defined in 

the OH-58 transmission as 105 output rotations.

Data Analysis

Initially, the strain data was inspected and it was determined 

that the signal was composed of two primary components, one 

low frequency, large amplitude component associated with the 

deformation of the ring during planet passes and a second high 

frequency small amplitude component associated with local 

tooth deformation. A technique for separating the two components was developed based on standard high/low pass filtering.

(a)

(b)

(c)

Figure 7.—Healthy vibration data collected from the OH-58C

transmission using a fiber optic strain sensor. (a) Raw 

data, (b) low frequency component, (c) high frequency 

component.

A representative raw strain signal and the resulting separated 

components are shown in Figure 7.

Signal-to-Noise Ratio

A comparison of signals from a strain sensor and a collocated accelerometer revealed that the raw strain signal had a 

significantly higher signal-to-noise ratio than the raw accelerometer signal as shown in Figure 8.

Tooth Meshes over One Carrier Cycle

Tooth Meshes over One Carrier Cycle

Tooth Meshes over One Carrier Cycle
NASA/TM—2011-217123 6

(a)

(b)

Figure 8.—Healthy vibration data collected from the NGRC 

OH-58 transmission using (a) an accelerometer and (b) a 

collocated fiber optic strain sensor.

Uncertainty Analysis

Further evaluation of the OH-58C strain data shows that the 

variation in the signal waveform appears to be exceptionally 

low from cycle-to-cycle. Figure 9 shows an overlay of 1200 

consecutive carrier cycles of strain data from a representative 

fiber optic strain sensor (strain sensor no. 1). The consistency 

of the waveform is evident as both the underlying ring strain 

signal and the individual tooth strain signals are clearly visible 

even when 1200 individual signals are overlaid.

Based on this consistency, our research shows that it is not 

necessary to average the data as is required for accelerometer 

data. Instead, it is possible that the condition indicators (CIs) 

may be applied directly to the unaveraged signal. This would 

significantly reduce the amount of data required to compute 

the various CIs and the amount of data gathering time needed 

to collect adequate data.

Considering that helicopter operations rarely stay in a particular flight condition for long, the sensor consistency 

coupled with multiple FBG sensors on a single array can 

greatly improve data quality by quickly gathering all of the 

required data in a much shorter period of time compared to 

accelerometers. For this study, both un-averaged and averaged 

data were analyzed.

(a)

(b)

Figure 9.—(a) Overlay of 1200 carrier cycles of strain data 

from fiber optic strain sensor no. 1. (b) Close-up of one 

planet pass lobe.

Vibration Separation

Vibration separation is a synchronous averaging technique 

that extracts individual vibration signals for the sun gear and 

each of the planet gears from the raw planetary gearbox vibration signal (Refs. 10 to 12). Since vibration separation is a form 

of synchronous averaging, it serves to enhance the features 

associated with the gear of interest while suppressing features 

associated with other components as well as noise. However, 

vibration separation has the added benefit that it indexes the 

teeth of the gear and assembles a signal associated with that 

gear that can more easily be used for damage detection.

As mentioned earlier, planetary gearbox vibration transducers are typically mounted on the gearbox housing, and are 

fixed relative to the moving planet gears and sun gear. When a 

planet passes close to a transducer, the amplitude of vibration 

measured by that transducer increases. The result is a region of 

increased amplitude, or a lobe, in the vibration signal associated with the passing of each planet. These lobes are clearly 

visible in the high frequency component of the fiber optic 

strain signal shown in Figure 7(c). Thus, data collected during 

one rotation of the planetary carrier will have a lobe for each 

planet; these lobes are often referred to as planet-pass lobes.

The vibration separation algorithm relies on two assumptions.

Tooth Meshes over One Carrier Cycle

Tooth Meshes over One Carrier Cycle

Tooth Meshes over One Carrier Cycle

Tooth Meshes
NASA/TM—2011-217123 7

1. The vibrations in each lobe region are predominately 

generated by the local planet gear meshing with the sun

and ring gear.

2. A hunting tooth ratio exists for the planet/ring gear pair 

and the sun/ring gear pair.

Given these assumptions, the vibration separation algorithm 

can be summarized in the following three steps.

1. A window is applied to each lobe to capture the segment 

of the signal dominated by the local planet gear.

2. The known geometry of the gearbox is used to index and 

arrange the windows sequentially according to either the 

progression of planet or sun teeth.

3. The windows are then assembled into a single vibration 

signal for each planet and for the sun.

Another key requirement for application of the vibration 

separation algorithm is that the raw vibration signal for each 

carrier cycle must have the same number of samples. Even 

small variations in the gearbox rpm will lead to a different 

number of samples in each carrier cycle signal. Thus, the data 

is interpolated (up-sampled) such that each tooth mesh is 

represented by 2n points. The value of n is chosen such that 2n

is the smallest number of points greater than that of the original data. This choice aids in the efficiency of the processing. 

The effect of various interpolation techniques on transmission 

vibration data has been studied and shown to be minimal

(Ref. 13). While down-sampling is generally preferred, upsampling is required in this case due to the low sampling 

frequency of the data. Thus, care is required in subsequent 

analysis of the data to ensure that high frequency features 

above the Nyquist frequency of the raw data are identified as 

artifacts of the processing rather than actual signal features.

A detailed description of the vibration separation algorithm 

is presented in References 10 to 12. However, it should be 

noted that in addition to suppressing non-salient features, the 

vibration separation algorithm also directly eliminates portions 

of the signal (through windowing) that do not contain salient 

information.

The primary variables in the implementation of the algorithm are the width and shape of the window applied to the 

planet pass lobes. In past work, it was found that for accelerometer vibration signals, a 4/5 Tukey window (total width of 

5 tooth meshes, flat center region of 1 tooth mesh and Gaussian tails of 2 tooth meshes on either side of flat center) 

produced the best representation of the planetary vibration 

signal (Ref. 11). During assembly, the tails of the 4/5 Tukey 

window overlap the two adjacent windows on either side. This 

overlap serves to minimize any discontinuities between data 

segments, as well as reinforcing the planetary vibration 

components through averaging. The indexing and arrangement 

of the windows ensures that vibration data segments generated 

by a given planet tooth are averaged only with other vibration 

data segments generated by the same tooth. 

Given the differences between the accelerometer data and 

the fiber optic strain data, it was not clear that the same 

window was appropriate for both types of data. It was hypothesized that the clean nature of the data would either 

increase the useful data in the tails of the planet pass lobe, or 

would reduce the size of discontinuities, enabling a smaller 

window with shorter tails to be used. Hence, three windows 

were chosen for evaluation.

1. Original Window: 4/5 Tukey window with a width of 5 

tooth meshes. 

2. Wide Window: 3/5 Tukey window with a total width of 

10 tooth meshes.

3. Narrow Window: 1/3 Tukey window with a width of 1.5 

tooth meshes.

The undamaged high-frequency component of the strain 

data was processed using the vibration separation algorithm 

with each of the three windows to generate planet vibration 

signals, and the frequency spectrum of the resulting planetary 

signals was evaluated and it was determined that the 10 tooth 

mesh window provided the most accurate reconstructed 

planetary signal. The 10 mesh wide window resulted in the 

lowest signal-to-noise ratio, and successfully captured the 

mesh frequency and first harmonic. The 5 mesh wide window 

had a higher signal-to-noise ratio and failed to capture the first 

harmonic. The 1.5 mesh wide window had a similar signal-tonoise ratio as the 5 mesh wide window, and indicated a 3rd 

and even 4th harmonic in addition to harmonics 1 and 2. As 

mentioned above, window overlap minimizes the discontinuities between adjacent signal segments. If the discontinuities 

are not sufficiently attenuated, then high frequency harmonics 

result. Recall that the earlier up-sampling would make it 

possible to see high frequency features not present in the 

original raw data. Given that the Nyquist frequency of the 

original raw data is between the second and third harmonics, 

any indication of a harmonic higher than the 2nd is an artifact 

of the assembly process. Since the 1.5 mesh wide window 

shows both a 2nd and 3rd harmonic, it is clear that it does not 

sufficiently attenuate the discontinuities. Thus, the 10 tooth 

mesh wide window was chosen for this research.

Once a separated vibration signal has been assembled, it is 

typically averaged with subsequent assembled vibration 

signals. However, as mentioned previously, further averaging 

of the strain data may not be necessary, and thus both unaveraged and averaged assembled signals were analyzed.

Damage Detection Results

A number of basic damage detection metrics were then 

computed using the resulting separated signals. For this case, 

30 subsequent separated signals were averaged. The condition 

indicators included in this project were the Kurtosis, FM0, 

FM4, M6A, M8A, the RMS Energy, the Crest Factor (CF), the 

Energy Operator (EO), and the Energy Ratio (ER). A summary of the metric description is provided in Reference 3.
NASA/TM—2011-217123 8

Figure 10.—Comparison of signal averaged condition indicator (SACI) values for the undamaged (green bars/left side) and the 

planet pinion tooth pitch line spall, ring-side (red bars/right side). Sensors 1-13 are shown for each planet.

As an example, the detection result for the planet tooth spall 

is shown in Figure 10. In this figure the increased amplitude of 

the red bars (right side of each planet response) over the 

amplitude of the baseline green bars (left side for each planet) 

for multiple metrics clearly indicates the damage on Planet 1. 

Specifically, FM4, M6A, M8A, and ER provide a strong 

indication of damage on Planet 1. In addition, FM0 and EO 

provide a weaker, though still clear, indication that the damage 

is on Planet 1.

From Figure 10, a large variation can be seen between different strain sensor locations. This may be caused by several 

factors, including the geometry of the transmission housing, 

location of the strain sensors relative to the ring gear teeth and 

the splines, band tension variability and fiber bonding variability. Overall, results from the damage detection analysis, by 

visually interpreting graphs similar to those shown in Figure 10

are shown in Table II.

For damage cases 1-5 and 1-6, pertaining to sun gear damage, 

the lack of detection capability is believed to be caused primarily 

because there is no hunting tooth ratio for relating sun gear teeth 

to the ring gear sensor position. The distance between the damage and the strain sensor location may also contribute to the lack 

of sensitivity. For the ring gear damage cases, 1-7 and 1-8, the no 

detection result was surprising to the authors.

It should be noted that this was an effort to assess the effectiveness for fiber optic strain monitoring and further optimization 

could be performed. Although some damage cases are listed as 

Marginal Confidence or No Detection, future efforts to improve 

the analysis and generate potentially new condition indicators 

specific to fiber optic strain-based sensors may improve the 

detection capability. Furthermore, advances in the fiber optic 

data collection instrumentation to allow for higher sampling rates 

will improve the likelihood of detecting some faults, specifically 

the bearing damage cases which are known to generate high 

frequency signals above those measured in this project.

1 2 3 4

0

1

2

3

4

Planet

SACI Kurtosis: 1-1 and 1-4B, Cond. 12

No Damage

Damage

1 2 3 4

0

2

4

6

8

Planet

SACI FM0: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

10

20

30

40

Planet

SACI FM4: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

500

1000

1500

2000

2500

3000

Planet

SACI M6A: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

0.5

1

1.5

2

2.5

x 105

Planet

SACI M8A: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

1

2

3

4

5

x 10-6

Planet

SACI RMS: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

1000

2000

3000

4000

5000

6000

Planet

SACI CF: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

5

10

15

20

Planet

SACI EO: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

0.05

0.1

0.15

0.2

Planet

SACI ER: 1-1 and 1-4B, Cond. 12
NASA/TM—2011-217123 9

TABLE II.—CONFIDENCE IN THE DAMAGE DETECTION RESULT FOR EACH DAMAGE CASE

Case Suggested confidence

1-2A: Planet pinion root crack, 25% depth, sun-side crack opening Moderate confidence

1-2B: Planet pinion root crack, 25% depth, ring-side crack opening Marginal confidence

1-3A: Planet pinion root crack, 50% depth, sun-side crack opening High confidence

1-3B: Planet pinion root crack, 50% depth, ring-side crack opening High confidence

1-4A: Planet pinion pitch line tooth spall, sun-side contact Moderate confidence

1-4B: Planet pinion pitch line tooth spall, ring-side contact High confidence

1-5: Sun gear root crack, 25% depth No detection

1-6: Sun gear pitch line tooth spall No detection

1-7: Ring gear root crack, 25% depth No detection

1-8: Ring gear root crack, 50% depth No detection

1-9: Planet bearing outer race pitting No detection

1-10: Planet bearing inner race pitting No detection

Effect of Averaging

The results presented above consider the case where 30 separated signals are averaged prior to applying the condition 

indicators. As mentioned previously, the high signal-to-noise 

and repeatability of the strain-based measurements provides an

opportunity to consider applying the damage metrics to a single 

separated signal. In Figure 11, the data is processed in this 

manner, with the condition indicators being averaged over the 

number of planet passes, as opposed to the vibration data being 

averaged prior to application of the indicators. The condition 

indicators are averaged to enable a concise display of results, 

and the one-sigma error is indicated to show the distribution.

For actual application, the condition indicators would not be 

averaged, but instead would be evaluated as they are computed.

It appears from Figure 11 that for this damage case, some of 

the averaged condition indicators may provide an indication of 

the presence of damage as well. Specifically, FM4, M6A and 

M8A appear to indicate damage. Hence, it is possible that 

condition indicators computed using unaveraged data could be 

used as an early indication of tooth spalling for teeth that come 

in contact with the ring gear. If the unaveraged condition 

indicator indicates damage, then more data could be collected 

and averaged to improve confidence in the detection result.

Torque Sensitivity

For every test case investigated in this project, data for four 

torque levels was collected. For all of the previous analysis, the 

highest torque level was used. This section focuses on the 

effect of changes in the torque level on the fiber optic strain 

vibration signals.

Figure 12(a) shows unaveraged vibration signals for the four 

torque levels for a single carrier cycle. Figure 12(b) shows the 

low frequency component of the signals, and Figure 12(c) 

shows the high frequency component of the signals. From these 

figures, it is evident that a change in torque has a clear effect on 

the amplitude of the vibration signal, as expected. However, 

comparing the low frequency and high frequency components, 

it appears that the effect on the amplitude of the low frequency 

ring deformation component is much greater than the effect on 

the amplitude of the high frequency tooth deformation component. 

This result suggests that the amplitude, either peak-to-peak 

or maximum, of the low frequency component of the strain 

signal could be correlated with the torque load on the transmission. This could be useful for direct usage monitoring.

As noted above, the effect of torque variation on the amplitude of the high frequency component of the strain signal is 

much smaller than on the low frequency component. However, 

this does not necessarily imply that damage detection performance will be unaffected. To evaluate the effect of torque 

variation on damage detection, the damage case which consists 

of a spall at the pitch line on the face of a single planet pinion 

tooth is selected for comparison with the baseline case 1-1. For 

this evaluation, the low torque data set is shown.

Figure 13 shows each of the condition indicator values for 

each planet compared with the undamaged baseline values for 

each planet. It is evident that this damage case can still be 

detected. However, the indication is not nearly as strong as in 

the high torque case shown in Figure 10.

Overall, these results indicate that the performance of the 

damage detection methodology may be affected by variations 

in torque and that a significant reduction in torque is detrimental to the damage detection performance even though the effect 

on the amplitude of the high frequency signal is minimal. 

However, it is possible that the torque sensitivity could be used 

to monitor the transmission torque, or more directly component 

strain, in real time and serve as input to a remaining useful life 

algorithm for usage monitoring. Thus it is recommended that 

the use of the low frequency signal for remaining useful life 

estimation be studied in a future research program.
NASA/TM—2011-217123 10

Figure 11.—Comparison of CI averaged condition indicator (CACI) values for the undamaged case (green bars/left side) and the 

planet pinion tooth pitch line spall, ring-side case (red bars/right side). Positive 1-σ error is Indicated by the black line. Sensors 1 -

13 are shown for each planet

1 2 3 4

0

1

2

3

4

5

Planet

CACI Kurtosis: 1-1 and 1-4B, Cond. 12

No Damage

Damage

+1 Sigma Error

1 2 3 4

0

2

4

6

8

10

12

Planet

CACI FM0: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

2

4

6

8

10

Planet

CACI FM4: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

50

100

150

200

250

300

Planet

CACI M6A: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

5000

10000

15000

Planet

CACI M8A: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

1

2

3

4

5

x 10-6

Planet

CACI RMS: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

1000

2000

3000

4000

5000

6000

Planet

CACI CF: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

5

10

15

Planet

CACI EO: 1-1 and 1-4B, Cond. 12

1 2 3 4

0

0.5

1

1.5

2

Planet

CACI ER: 1-1 and 1-4B, Cond. 12
NASA/TM—2011-217123 11

(a)

(b)

(c)

Figure 12.—Comparison of one carrier cycle for four different torque 

levels, (a) Raw signal, (b) low frequency vibration signal component, (c) high frequency vibration signal component.

0 10 20 30 40 50 60 70 80 90

Ring Tooth

0.12

- 0.06

0 10 20 30 40 50 60 70 80 90

Ring Tooth

0.1

- 0.06

0 10 20 30 40 50 60 70 80 90

Ring Tooth

0 10 20 30 40 50 60 70 80 90

0 10 20 30 40 50 60 70 80 90

0 10 20 30 40 50 60 70 80 90

0.01

- 0.01

0.01

- 0.01

0.01

- 0.01

0.01

- 0.01
NASA/TM—2011-217123 12

Figure 13.—Comparison of signal averaged condition indicator (SACI) values for low torque (854 in-lb) condition for the undamaged 

case (green bars/left side) and the planet pinion tooth pitch line spall, ring-side case (red bars/right side). Sensors 1 - 13 are 

shown for each planet.

1 2 3 4

0

1

2

3

4

Planet

SACI Kurtosis: 1-1 and 1-4B, Cond. 09

No Damage

Damage

1 2 3 4

0

1

2

3

4

5

6

Planet

SACI FM0: 1-1 and 1-4B, Cond. 09

1 2 3 4

0

5

10

15

20

Planet

SACI FM4: 1-1 and 1-4B, Cond. 09

1 2 3 4

0

200

400

600

800

Planet

SACI M6A: 1-1 and 1-4B, Cond. 09

1 2 3 4

0

1

2

3

4

x 104

Planet

SACI M8A: 1-1 and 1-4B, Cond. 09

1 2 3 4

0

0.5

1

1.5

2

x 10-6

Planet

SACI RMS: 1-1 and 1-4B, Cond. 09

1 2 3 4

0

2000

4000

6000

8000

10000

12000

Planet

SACI CF: 1-1 and 1-4B, Cond. 09

1 2 3 4

0

1

2

3

4

5

Planet

SACI EO: 1-1 and 1-4B, Cond. 09

1 2 3 4

0

0.02

0.04

0.06

0.08

0.1

0.12

Planet

SACI ER: 1-1 and 1-4B, Cond. 09
NASA/TM—2011-217123 13

(a)

(b)

(c)

Figure 14.—Comparison of 1-carrier cycle raw vibration signal 

for mast load off and mast load on conditions. (a) Raw signal, (b) low frequency component, (c) high frequency component

Mast Loading Sensitivity

For each test case investigated in this project, data with the 

mast load both on and off were collected. The mast load in this 

project consisted of both a mast lift and mast bending load 

applied simultaneously. For the previous results, the case with 

no mast load was used. 

Figure 14(a) shows unaveraged vibration signals for the mast 

load on and off cases for a single carrier cycle. Figure 14(b)

shows the low frequency component of the signals, and Figure

14(c) shows the high frequency component of the signals. From 

these figures, it appears that the mast load has a negligible 

effect on the raw strain signal as well as both the high and low 

frequency components of the signal. Calculation of the condition indicators confirms that mast loading does not affect 

damage detection.

Summary and Conclusion

This paper is focused on the use of a Fiber Optic Strain Sensor Array for detecting damage in the planetary stage of a 

helicopter transmission. A removable band-type of sensor was 

developed for use with fiber Bragg grating sensors. With 

modifications to the ring gear and transmission housing, the 

sensor array was installed on a Bell OH-58C transmission at 

the NASA Glenn Helicopter Transmission Test Facility.

Testing of the fiber optic sensor array was performed 

throughout a series of tests that consisted of baseline and 

multiple damage cases including cracks and spalls of the 

planetary gears. Testing of each damage case was performed 

over a range of torque loads with and without mast loading.

Analysis of the resulting strain signals shows extremely repeatable measurements with high signal-to-noise ratio as compared 

to conventional accelerometer measurements.

Damage detection was performed on the high frequency 

component of the strain signal using condition indicators 

previously developed for accelerometer-based measurements.

Using these indicators, the fiber optic strain measurements are 

capable of detecting several types of damage including planet 

gear cracks and spalls. However the technique shows limitation 

in detecting other damage cases such as damaged sun gears and 

bearing race pitting.

The fiber optic strain measurements also show strong correlation with torque loading. Although this leads to a decreased 

damage sensitivity at low torque levels, it also provides a 

potential new type of torque measurement technique. No effect 

was detected with mast loading.

References

1. Giurgiutiu, V., Cuc, A., and Goodman, P., “Review of Vibration-Based Helicopters Health and Usage Monitoring Methods,” 

Proceeding of the 55th Meeting of the Society for Machinery 

Failure Prevention Technology, April 2–5, 2001, Virginia 

Beach, VA.

0 10 20 30 40 50 60 70 80 90

Ring Tooth

0.12

- 0.06

0 10 20 30 40 50 60 70 80 90

Ring Tooth

0.1

- 0.06

0 10 20 30 40 50 60 70 80 90

Ring Tooth

0.02

0.02

- 0.02

- 0.020 10 20 30 40 50 60 70 80 90
NASA/TM—2011-217123 14

2. Zakrajsek, J., et al., “Rotorcraft Health Management Issues and 

Challenges,” prepared for the First International Forum on Integrated System Health Engineering and Management in Aerospace, cosponsored by NASA Ames Research Center and 

Marshall Space Flight Center, Napa, CA, Nov. 7–10, 2005, 

NASA/TM—2006-214022.

3. Samuel, P., and Pines, D., “A Review of Vibration Based Techniques for Helicopter Transmission Diagnostics,” Journal of 

Sound and Vibration, Vol. 282, 2005, pp. 475–508.

4. Othonos, A., and Kalli, K., “Fiber Bragg Gratings: Fundamentals and Applications in Telecommunications and Sensing,” 

Artech House, Inc., London, United Kingdom, ISBN 0-89006-

344-3, 1999.

5. Baldwin, C., Kiddy, J., Samuel, P., Coker, J., and Pines, D., 

“Fiber Optic Sensors Monitoring Transmission Ring Gears,”

Proceedings of the SPIE Optics East Conference, Boston, MA, 

2007.

6. Coker, J., Pines, D., Samuel, P., Kiddy, J. and Baldwin, C., 

“Fiber Bragg Gratings for Detection of Planetary Gear Damage 

in Helicopter Transmissions,” Proceedings of the Fifth International Conference on Condition Monitoring and Machinery 

Failure Prevention Technology, Edinburgh, United Kingdom, 

2008.

7. Coker, J., Pines, D., Samuel, P.D., and Kiddy, J., 2008, “Fiber 

Optic Strain Sensor Vibration Separation for Detection of 

Seeded Faults in Rotorcraft Transmissions,” Proceedings of the 

ASME SMASIS Conference, Ellicott City, MD.

8. Lewicki, D., and Woods, R., “Evaluation of Low-Noise, Improved-Bearing-Contact Spiral Bevel Gears,” Proceedings of 

the 59th American Helicopter Society Annual Forum, Phoenix,

AZ, May 2003.

9. R. Kashyap: Fiber Bragg Gratings, Academic Press, San Diego, 

CA, 1999. 

10. Samuel, P., “Helicopter Transmission Diagnostics using Constrained Adaptive Lifting,” Ph.D. Dissertation, University of 

Maryland, College Park, MD, Aug. 2003.

11. McFadden, P., “A Technique for Calculating the Time Domain 

Averages of the Vibration of the Individual Planet Gears and 

Sun Gear in an Epicyclic Gearbox,” Journal of Sound and Vibration, Vol. 144, (1), 1991, pp. 163–172.

12. Samuel, P. and Pines, D., “Vibration Separation and Diagnostics 

of Planetary Geartrains,” Proceedings of the AHS 56th Forum, 

Virginia Beach, VA, May 2–4, 2000.

13. Decker, H., and Zakrajsek, J., “Comparison of Interpolation 

Methods as Applied to Time Synchronous Averaging,”

NASA/ARL Technical Report, NASA/TM—1999-209086, 

ARL–TR–1960, 1999.
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Fiber Optic Strain Sensor for Planetary Gear Diagnostics 

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Kiddy, Jason, S.; Samuel, Paul, D.; Lewicki, David, G.; LaBerge, Kelsen, E.; Ehinger, Ryan, 

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13. SUPPLEMENTARY NOTES

14. ABSTRACT

This paper presents a new sensing approach for helicopter damage detection in the planetary stage of a helicopter transmission based on a 

fiber optic strain sensor array. Complete helicopter transmission damage detection has proven itself a difficult task due to the complex 

geometry of the planetary reduction stage. The crowded and complex nature of the gearbox interior does not allow for attachment of sensors 

within the rotating frame. Hence, traditional vibration-based diagnostics are instead based on measurements from exter-nally mounted 

sensors, typically accelerometers, fixed to the gearbox exterior. However, this type of sensor is susceptible to a number of external 

disturbances that can corrupt the data, leading to false positives or missed detection of potentially catastrophic faults. Fiber optic strain 

sensors represent an appealing alternative to the accelerometer. Their small size and multiplexibility allows for potentially greater sensing 

resolution and accuracy, as well as redundancy, when employed as an array of sensors. The work presented in this paper is focused on the 

detection of gear damage in the planetary stage of a helicopter transmission using a fiber optic strain sensor band. The sensor band includes 

an array of 13 strain sensors, and is mounted on the ring gear of a Bell Helicopter OH-58C transmission. Data collected from the sensor 

array is compared to accelerometer data, and the damage detection results are presented.

15. SUBJECT TERMS

Transmissions (machine element); Fiber optics; Gears; Detection 

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