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Present: Erfan ZakerEsfahani
Email: aref_z_e@yahoo.com
Number: ----------------
Lecturer: Dr. saatchi
University: najaf abad
Numberof student: 890914688
Course: Corrosion in Natural Environments
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outlineoutline
IntroductionIntroduction
Sensor ConceptsSensor Concepts
SENSOR TYPESSENSOR TYPES
Corrosion MonitoringCorrosion Monitoring
intelligent corrosion sensor (ICS)intelligent corrosion sensor (ICS)
Microwave Corrosion DetectorMicrowave Corrosion Detector
6 CONCLUSIONSCONCLUSIONS
7 REFERENCESREFERENCES
AbstractAbstract
• Corrosion is one major factor for high maintenance cost and
premature equipment failures.
•Life prediction of structural and functional performance of
materials is vital to safe, reliable and effective operation of aircraft,
ships and other weapon systems.
•Use of sensors to find corrosion is the best option by which early
detection and monitoring is possible.
•These are wireless autonomous intelligent corrosion sensor (ICS)
and microwave corrosion detector.
•Examples where such sensors have been used on military aircraft
for test and validation purposes have been given.
•The corrosion related costs to the department of defense in the United States exceed over $20
billions per year . The majority of it is due to periodic or scheduled operational and depot
maintenance and repair. In essence this cost has gone above the new equipment acquisition
cost.
•Online inspection tools, leave-in-place sensors and devices for damage detection and
monitoring may perhaps shift the paradigm on scheduled maintenance and proactive remedial
actions. In corporating and/or embedding all kinds of sensors and extracting corrosion
information are proper solutions.
•Knowing the problem means significant cost savings, and for the military it means good
reliability and mission readiness .Sensors can predict when environmental conditions can be
conducive to corrosion and when an action should be warranted as cost effective and best in
the interest of safety, reliability and survivability. Sensors could do away with scheduled or
periodic depot maintenance or PDM cycle as maintenance action would then be condition
based.
•Corrosion on aircraft occurs in several forms. The galvanic, crevice and pitting corrosion types
are most abundant occurrences. Exfoliation or intergranular corrosion at joints, overlaps and
edges are most repaired forms of damage. Stress corrosion cracking (SCC), corrosion fatigue
(CF) and hydrogen embrittlement (HE) are concomitant phenomena with initiation of pits and
crevices where structure is under high stress and load.
(i) the localized environmental condition,
(ii) the types of materials and designs used,
(iii) the concentration of stresses and strains,
(iv) the corrosion prevention and control processes
adopted,
(iv) their service performance history,
and (v) development of a database from which various
assertions can be made.
Figure 1 – Hidden Corrosion damage on aircraft showing excessive growth of corrosion product
under the skin (aluminum sheet), bulging around the holes and intergranular (exfoliation)
corrosion at the edge of a structural joint (frame).
Pillowing (skin bulging) around fasteners
Essentially, there are only two classes of diagnostic tools: one that defines and monitors the
corrosive condition or environment in which an equipment operates/performs, and the second
that detects and/or determines where an active corrosion or corrosion related damage has
occurred.
These types of sensors help resolve and set the endurance limits of the materials/structures used
in a corrosion susceptible environment; in particular, for materials with high threshold for SCC,
CF and HE.
A sensor can detect and quantify corrosion causing elements, corrosion products, forms of
corrosion, mass or thickness loss, pit count and depth, crack sizes and coating or composite
disbond. For reasons of limitations, only a select few are discussed below.
SENSOR TYPES
This type sensor usually measures electrochemical change in the galvanic current, potential
or resistance of one of the sensing element as it reacts with the corrosive nature of the
environment. This current, potential or resistance output can be logged or monitored to
develop a real time corrosion exposure profile and help create a database for analysis and future
reference.
Such sensors determine early signs of expected hidden corrosion. The intelligent corrosivity
sensor (ICS) is such a device developed by this author that is wireless and autonomous.
The Figure 2 shows the essential components of the ICS system: a bimetallic thin film sensing
element, an electronic module (a micro controller for data collection, storage and
transmission), and a transponder for RF communication, programming and data download to
laptop computer.
CCC
pretreated
coupon
sandwich test
coupon:
inside view.
Cr(III)
pretreated
sandwich
test coupon:
inside
view.
ICS Data Gathering
Transponder (DGT)
Figure 2 – The ICS system components and assembly
DGT, RS-232 serial cable and
Fully assembled sensor unitFully assembled sensor unit
Electronic Module
Bi-metallic thin film sensorBi-metallic thin film sensor
The thin-film bimetallic sensing element is comprised of interdigitated alternate strips of active
and passive metals on a non-conducting polymer, e.g. gold and cadmium on a kapton film. For
sensor to work, it only takes a small amount of moisture (above 50% RH) in the air to condense
on it and cause corrosion of the anodic element of the sensing couple.
This galvanic corrosion current is picked up by the electronic module and recorded in real time.
The magnitude of this current depends on the nature of condensed film, more corrosive the
nature, higher the current.
The very first actual testing of corrosivity sensors was performed on a P-3C Orion aircraft. A
number of sensors were installed as shown in Figure 4 to monitor areas that were identified as
most corrosion prone or susceptible. These aircraft are stationed in shore locations and fly
over the water at low altitude. The data collected over a period of four months showed most
corrosion activity in the sensor location 3, 5 and 6. The plots in Figure 5 show the charge
transients collected in coulomb by each sensor during thedeployment. Based on observations ,
locations 3 and 5 were the corrosive environment cites and concurred with the sensor data
recorded.
log(Current)
Coulombs
CurrentvsTime6/19/02
1.000E-08
1.000E-07
1.000E-06
0.0 24.0 48.0 72.0 96.0 120.0
Time(Hrs)
Sensor90 Sensor43
CoulombsvsTime6/19/02
0.05000000
0.00000000
0.10000000
0.15000000
0.0 24.0 96.0 120.048.0 72.0
Time(Hrs)
Sensor90 Sensor43
Figure 3 - Results of ICS testing in a cyclic humidity cabinet alternating between 25% and 90%
relative humidity and at temperatures of 25° and 35° C, respectively.
Sensor #8
Equipment Rack E-1
Sensor #6
Aft Main
Ring Fitting
Sensor #5
Forward Main
Sensor #4
Sensor #3
Horizontal
Stab Skin
F.S. 323
Sensor #1
Outboard Nacelle
Sensor #7
Heat Exchanger
Sensor #2
Figure 4 - Corrosivity monitoring aboard a P-3C Orion aircraft. Squares in red show the
location where thin film sensors are installed in the interior.
CorrosionCorrosion MonitoringMonitoring
The same thin film device has been modified to measure corrosion of the structure to which it has
been attached. The difference in this modification was that the anodic element of the thin film
sensor was disconnected or removed. In other words, the cadmium deposits from the interdigitated
sensor were chemically removed and the structural metal was used as anode instead (cf. Figure 5).
The cathode elements remained the same, i.e. gold strips.
The modified sensor shown above now forms a galvanic couple between the actual aluminum
structural plate and the gold strips of the thin film sensor. When installation in joints, two pieces of
2-mil thick scrimcloth are used as separators on either side of the thin film sensor and sandwiched
between the two Al plates (cf. Figure 5).
Use of scrim cloth serves to separate sensing elements and busline and performs as a micro-cell for
ionic conduction when moisture/salt intrusion takes place. For data collection, the ICS function
remained the same as before, but with the difference that the galvanic current recorded is now
generated from the corrosion of aluminum plate and not from the anodic elements of the sensor. A
schematic drawing of the experimental set-up of how this was done is shown in Figure 6.
Cathode Element
Top metal plate
top aluminum plate
Element
Figure 5 - Schematic of thin film sensor sandwich for active corrosion monitoring.
Scrim cloth
Scrim cloth
Cathode
Anode Contact
Bottom plate
Channel 1
Channel 2
Channel 3
Channel 5
Channel 6
Cumulative Coulombs vs. Time, US Navy P-3, #322, Brunswick
NAS, Cummulative 1999
1.4
1.2
1
0.8
0.6
0.4
0.2
0
Figure 6 – Sensor output in coulombs with exposure time from various sensors installed at
locations on a P-3C Orion aircraft.
Figure 7 – Modified thin film sensor with removed anodic elements and contact point.
104.5
109.0
113.6
118.1
122.6
13.6
18.2
22.7
27.3
31.8
36.4
40.9
45.4
50.0
54.5
59.1
63.6
68.1
72.7
77.2
81.8
86.3
90.9
95.4
99.9
0.0
4.6
9.1
Time (Days)
Coulombs
Figure 8– Six aluminum plate sandwich assemblies containing sensors in its cavity and attached
with ICSs for monitoring internal corrosion of aluminum due environmental intrusion.
After connecting the sensors as shown in Figure 5 schematic, the Al 7075-T6 test coupons
(plates) were pneumatically riveted with high strength aluminum rivets. In order to simulate
typical aircraft installation, the joints were sealed with RTV along the edges but no sealant was
applied around the fasteners. The whole assembly was then coated with epoxy primer and
polyurethane topcoat. Six such test specimens were prepared and exposed inside a salt fog
cabinet (ASTM B-117 Test Method) as shown in Figure 11 for corrosion testing.
Corrosion Damage
Coulombs
Figure 9– Sensor output and field data correlation chart to determine maintenance action.
Once a lot of sensor data are generated in the field, the next step is to develop a process by which
one can analyze the results to make a maintenance decision. Perhaps, one of the ways is to create a
master chart from the field and laboratory data like one shown in Figure 9.
Data Analysis
The identification of threshold by color-coded signal blocks, such as blue yellow and red would
indicate the increasing corrosion severity and corrosion susceptibility.
Development of such correlation charts for all missions and all types of sensors used to measure
material damage in a given environment for different alloy systems is absolutely necessary for
correlation between corrosivity and corrosion damage.
Microwave Corrosion Detector
Microwave devices sense corrosion under coatings by detecting a change in the dielectric
characteristics that result from the formation of oxides (which are dielectric in nature) in
corroded areas. The Microwave Corrosion Detector (MCD) is a handheld battery powered tool
that operates much like an electronic stud finder.
As the operator passes the MCD over a painted surface (organic coating) under which corrosion
is present its display lights up to indicate the severity of the corrosion detected. The system also
provides Geiger counter-like chip feedback to the operator through an earphone jack. A serial
connection provides PC recording and analysis capabilities for corrosion trend monitoring.
MCD outputs include:
1- a corrosion severity indicator and
2- the distance to bare metal from atop the coating.
The principle of microwave detection is based:
1- on the dielectric change or
2-loss of energy from the reflected surfaces.
The MCD is a self-contained, handheld NDT system
Figure 9– Hand held MCD for corrosion detection under coatings
Figure 10 - The schematic of microwave incident and reflected signals from atop the coating.
The MCD senses these changes by comparing the incident and reflected microwave signals as
they pass through the coating (paint) system and reflect off the aircraft’s metal substrate (see
Figure 10).
The MCD is powered by three internal AA batteries and can operate for up to 10 hours. It has a
serial port to facilitate interconnection with a PDA, laptop, or PC for data recording and
advanced real time displays. Both onboard and laptop supporting software can be customized
for a wide variety of inspection scenarios. For corrosion under paints, the MCD is placed on the
surface and moved by sliding for some reasonable length and then moved up or down to cover
a specific area and storing the information. The reflected energy spectra can be stored in the
computer during scanning for a reference and quantification. The results shown in Figure 11
were obtained by scanning over laths of corrosion on aluminum 7075-T6 plates that had
undergone salt fog exposure.
Figure 11- Dual mode laptop display of corrosion severity and damage on a 0.007 in
thick painted Al 7075-T6 metal surface.
Currently, a broad variety of corrosion detection and monitoring devices are available.
The list shown below is a summary of them, starting from visual/optical type to those
involving ultrasonics, microwave, thermal to chemical and electrochemical as
detection methods and mechanisms.
Visual/Optical Inspection – a sentry method using fiber optics (boroscope)
 D-Sight, Edge of Light CCD (Charge Coupled Devices) video scanners and image analyzers
 Guided Wave Ultrasonics and Ultrasound Imaging
Acoustic Methods – using surface acoustic wave (SAW) device
 Multifrequency Eddy Current
Radiography - Neutron, Digital and X-Rays (low level - source)ϒ
 Microwave Scanner, Dielectrometer
 Thermal and Infrared Imaging (IR), Tomography
Magneto-optic Eddy Current Imaging
 Magnetic Particles, Magnetometer, SQUID, Magnetic Flux
Electrical Methods – probes measuring resistance or potential change
 Electrochemical Methods – using sensors that measure galvanic current, potential,
resistance, and electrochemical impedance and noise
Chemical Sensors - fluorescence and redox indicators, liquid penetrant, light obscurance,
holographic interferometry
 Other Miscellaneous Techniques - coulometry, calorimetry, etc.
CONCLUSIONSCONCLUSIONS
The sensor systems described in this paper perform two distinct functions:
1- measure corrosive nature of the environment present and
2- monitor the corrosion damage in hidden areas of aircraft and under coatings.
REFERENCES
1. “Opportunities to Reduce Corrosion Costs and Increase Readiness”, Report to Congressional Committee, US General Accounting Office
Report GAO-03-753, July 2003.
2. V.S. Agarwala and S. Ahmad, “Corrosion Detection and Monitoring – A Review”, CORROSION/2000, Paper No.271, 2000, NACE
International, Houston, TX.
3. V.S. Agarwala, “Sensors for Monitoring Aircraft Corrosion Health”, Proceedings of 14th
International Corrosion Congress, Paper No. 245.1,
Sept. 27, 1999, Cape Town, South Africa; “In- Situ Corrosivity Monitoring of Military Hardware”, CORROSION/1996, Paper No. 632, 1996, NACE
International, Houston, TX.
4. J.L. Rose, L.E. Soley, Tom Hay and V.S. Agarwala, “Ultrasonic Guided Waves for Hidden Corrosion Detection in Naval Aircraft”,
CORROSION/2000, Paper No. 267, 2000, NACE International, Houston, TX.
5. Ignacio Perez and Paul Kulowitch, “Thermography Characterization of Corrosion Damage”, CORROSION/2000, Paper No. 290, 2000, NACE
International, Houston, TX.
6. M. Twomey, “Inspection Techniques for Detecting Corrosion Under Insulation”, Material Evaluation, Vol. 55,129-33, 1997.
7. Neil Goldfine, “Enhancements in MWM-Array Hidden Corrosion Imaging”, Proceedings of 2003 Tri-Service Corrosion Conference, Las Vegas,
NV, Session XVII, November 2003, Naval Air Systems Command, Patuxent River, MD.
8. Alan Bray, H. Stretz and S.C. Buckner, “Coating Effects in Microwave NDE in the Detection of Corrosion for Aircraft Application”,
CORROSION/2000, Paper No. 268, 2000, NACE International, Houston, TX; “Microwave NDE Tool Development and Beta Testing”, Proceedings
of 2003 Tri- Service Conference, Las Vegas, NV, Session XIII, November 2003, Naval Air Systems Command, Patuxent River, MD.
9. G.D. Davis, C.M. Dacres and L.A. Krebs, “EIS-Based In-Situ Sensors for the Early Detection of Coatings Degradation and Substrate
Corrosion” CORROSION/2000, Paper No. 275, 2000, NACE International, Houston, TX.
10. J.N. Schoess, “Smart Fastener for KC-135 Structural Integrity Monitoring”, 1997 SPIE Smart Structures and Materials Conference, March 1,
1997.
11. Anna A. Panova, P. Pantano and D.R. Walt, “In-Situ Florescence Imaging of Localized Corrosion with a Ph Sensitive Imaging Fiber”,
Analytical Chemistry, 69, 1635-1641, 1997.
12. R. Wood and R. Waldrop, “Infrared Thermal Imaging as a Tool for the Characterization of Corrosion”, Proceedings of 2003 Tri-Service
Corrosion Conference, Las Vegas, NV, Session XVII, November 2003, Naval Air Systems Command, Patuxent River, MD.
13. D. Dixon, S. J. Harris, J.E. Cole, B.R.W. Hinton, et.al. “A Corrosion Prediction Model and Corrosion Sensor for Corrosion Management”,
Proceedings of 2003 Tri-Service Corrosion Conference, Las Vegas, NV, Session F, November 2003, Naval Air Systems Command, Patuxent
River, MD.
hank you for your attentiohank you for your attentio
May 2012
Erfan Zaker
Esfahani

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Electrochemical Bimetallic Galvanic Sensor

  • 1. Present: Erfan ZakerEsfahani Email: aref_z_e@yahoo.com Number: ---------------- Lecturer: Dr. saatchi University: najaf abad Numberof student: 890914688 Course: Corrosion in Natural Environments
  • 2. 1 2 3 4 5 outlineoutline IntroductionIntroduction Sensor ConceptsSensor Concepts SENSOR TYPESSENSOR TYPES Corrosion MonitoringCorrosion Monitoring intelligent corrosion sensor (ICS)intelligent corrosion sensor (ICS) Microwave Corrosion DetectorMicrowave Corrosion Detector 6 CONCLUSIONSCONCLUSIONS 7 REFERENCESREFERENCES AbstractAbstract
  • 3. • Corrosion is one major factor for high maintenance cost and premature equipment failures. •Life prediction of structural and functional performance of materials is vital to safe, reliable and effective operation of aircraft, ships and other weapon systems. •Use of sensors to find corrosion is the best option by which early detection and monitoring is possible. •These are wireless autonomous intelligent corrosion sensor (ICS) and microwave corrosion detector. •Examples where such sensors have been used on military aircraft for test and validation purposes have been given.
  • 4. •The corrosion related costs to the department of defense in the United States exceed over $20 billions per year . The majority of it is due to periodic or scheduled operational and depot maintenance and repair. In essence this cost has gone above the new equipment acquisition cost. •Online inspection tools, leave-in-place sensors and devices for damage detection and monitoring may perhaps shift the paradigm on scheduled maintenance and proactive remedial actions. In corporating and/or embedding all kinds of sensors and extracting corrosion information are proper solutions. •Knowing the problem means significant cost savings, and for the military it means good reliability and mission readiness .Sensors can predict when environmental conditions can be conducive to corrosion and when an action should be warranted as cost effective and best in the interest of safety, reliability and survivability. Sensors could do away with scheduled or periodic depot maintenance or PDM cycle as maintenance action would then be condition based. •Corrosion on aircraft occurs in several forms. The galvanic, crevice and pitting corrosion types are most abundant occurrences. Exfoliation or intergranular corrosion at joints, overlaps and edges are most repaired forms of damage. Stress corrosion cracking (SCC), corrosion fatigue (CF) and hydrogen embrittlement (HE) are concomitant phenomena with initiation of pits and crevices where structure is under high stress and load.
  • 5. (i) the localized environmental condition, (ii) the types of materials and designs used, (iii) the concentration of stresses and strains, (iv) the corrosion prevention and control processes adopted, (iv) their service performance history, and (v) development of a database from which various assertions can be made.
  • 6. Figure 1 – Hidden Corrosion damage on aircraft showing excessive growth of corrosion product under the skin (aluminum sheet), bulging around the holes and intergranular (exfoliation) corrosion at the edge of a structural joint (frame). Pillowing (skin bulging) around fasteners
  • 7. Essentially, there are only two classes of diagnostic tools: one that defines and monitors the corrosive condition or environment in which an equipment operates/performs, and the second that detects and/or determines where an active corrosion or corrosion related damage has occurred. These types of sensors help resolve and set the endurance limits of the materials/structures used in a corrosion susceptible environment; in particular, for materials with high threshold for SCC, CF and HE. A sensor can detect and quantify corrosion causing elements, corrosion products, forms of corrosion, mass or thickness loss, pit count and depth, crack sizes and coating or composite disbond. For reasons of limitations, only a select few are discussed below.
  • 8. SENSOR TYPES This type sensor usually measures electrochemical change in the galvanic current, potential or resistance of one of the sensing element as it reacts with the corrosive nature of the environment. This current, potential or resistance output can be logged or monitored to develop a real time corrosion exposure profile and help create a database for analysis and future reference. Such sensors determine early signs of expected hidden corrosion. The intelligent corrosivity sensor (ICS) is such a device developed by this author that is wireless and autonomous. The Figure 2 shows the essential components of the ICS system: a bimetallic thin film sensing element, an electronic module (a micro controller for data collection, storage and transmission), and a transponder for RF communication, programming and data download to laptop computer. CCC pretreated coupon sandwich test coupon: inside view. Cr(III) pretreated sandwich test coupon: inside view.
  • 9. ICS Data Gathering Transponder (DGT) Figure 2 – The ICS system components and assembly DGT, RS-232 serial cable and Fully assembled sensor unitFully assembled sensor unit Electronic Module Bi-metallic thin film sensorBi-metallic thin film sensor
  • 10. The thin-film bimetallic sensing element is comprised of interdigitated alternate strips of active and passive metals on a non-conducting polymer, e.g. gold and cadmium on a kapton film. For sensor to work, it only takes a small amount of moisture (above 50% RH) in the air to condense on it and cause corrosion of the anodic element of the sensing couple. This galvanic corrosion current is picked up by the electronic module and recorded in real time. The magnitude of this current depends on the nature of condensed film, more corrosive the nature, higher the current. The very first actual testing of corrosivity sensors was performed on a P-3C Orion aircraft. A number of sensors were installed as shown in Figure 4 to monitor areas that were identified as most corrosion prone or susceptible. These aircraft are stationed in shore locations and fly over the water at low altitude. The data collected over a period of four months showed most corrosion activity in the sensor location 3, 5 and 6. The plots in Figure 5 show the charge transients collected in coulomb by each sensor during thedeployment. Based on observations , locations 3 and 5 were the corrosive environment cites and concurred with the sensor data recorded.
  • 11. log(Current) Coulombs CurrentvsTime6/19/02 1.000E-08 1.000E-07 1.000E-06 0.0 24.0 48.0 72.0 96.0 120.0 Time(Hrs) Sensor90 Sensor43 CoulombsvsTime6/19/02 0.05000000 0.00000000 0.10000000 0.15000000 0.0 24.0 96.0 120.048.0 72.0 Time(Hrs) Sensor90 Sensor43 Figure 3 - Results of ICS testing in a cyclic humidity cabinet alternating between 25% and 90% relative humidity and at temperatures of 25° and 35° C, respectively. Sensor #8 Equipment Rack E-1 Sensor #6 Aft Main Ring Fitting Sensor #5 Forward Main Sensor #4 Sensor #3 Horizontal Stab Skin F.S. 323 Sensor #1 Outboard Nacelle Sensor #7 Heat Exchanger Sensor #2 Figure 4 - Corrosivity monitoring aboard a P-3C Orion aircraft. Squares in red show the location where thin film sensors are installed in the interior.
  • 12. CorrosionCorrosion MonitoringMonitoring The same thin film device has been modified to measure corrosion of the structure to which it has been attached. The difference in this modification was that the anodic element of the thin film sensor was disconnected or removed. In other words, the cadmium deposits from the interdigitated sensor were chemically removed and the structural metal was used as anode instead (cf. Figure 5). The cathode elements remained the same, i.e. gold strips. The modified sensor shown above now forms a galvanic couple between the actual aluminum structural plate and the gold strips of the thin film sensor. When installation in joints, two pieces of 2-mil thick scrimcloth are used as separators on either side of the thin film sensor and sandwiched between the two Al plates (cf. Figure 5). Use of scrim cloth serves to separate sensing elements and busline and performs as a micro-cell for ionic conduction when moisture/salt intrusion takes place. For data collection, the ICS function remained the same as before, but with the difference that the galvanic current recorded is now generated from the corrosion of aluminum plate and not from the anodic elements of the sensor. A schematic drawing of the experimental set-up of how this was done is shown in Figure 6. Cathode Element Top metal plate top aluminum plate Element Figure 5 - Schematic of thin film sensor sandwich for active corrosion monitoring. Scrim cloth Scrim cloth Cathode Anode Contact Bottom plate
  • 13. Channel 1 Channel 2 Channel 3 Channel 5 Channel 6 Cumulative Coulombs vs. Time, US Navy P-3, #322, Brunswick NAS, Cummulative 1999 1.4 1.2 1 0.8 0.6 0.4 0.2 0 Figure 6 – Sensor output in coulombs with exposure time from various sensors installed at locations on a P-3C Orion aircraft. Figure 7 – Modified thin film sensor with removed anodic elements and contact point. 104.5 109.0 113.6 118.1 122.6 13.6 18.2 22.7 27.3 31.8 36.4 40.9 45.4 50.0 54.5 59.1 63.6 68.1 72.7 77.2 81.8 86.3 90.9 95.4 99.9 0.0 4.6 9.1 Time (Days) Coulombs
  • 14. Figure 8– Six aluminum plate sandwich assemblies containing sensors in its cavity and attached with ICSs for monitoring internal corrosion of aluminum due environmental intrusion. After connecting the sensors as shown in Figure 5 schematic, the Al 7075-T6 test coupons (plates) were pneumatically riveted with high strength aluminum rivets. In order to simulate typical aircraft installation, the joints were sealed with RTV along the edges but no sealant was applied around the fasteners. The whole assembly was then coated with epoxy primer and polyurethane topcoat. Six such test specimens were prepared and exposed inside a salt fog cabinet (ASTM B-117 Test Method) as shown in Figure 11 for corrosion testing.
  • 15. Corrosion Damage Coulombs Figure 9– Sensor output and field data correlation chart to determine maintenance action. Once a lot of sensor data are generated in the field, the next step is to develop a process by which one can analyze the results to make a maintenance decision. Perhaps, one of the ways is to create a master chart from the field and laboratory data like one shown in Figure 9. Data Analysis The identification of threshold by color-coded signal blocks, such as blue yellow and red would indicate the increasing corrosion severity and corrosion susceptibility. Development of such correlation charts for all missions and all types of sensors used to measure material damage in a given environment for different alloy systems is absolutely necessary for correlation between corrosivity and corrosion damage.
  • 16. Microwave Corrosion Detector Microwave devices sense corrosion under coatings by detecting a change in the dielectric characteristics that result from the formation of oxides (which are dielectric in nature) in corroded areas. The Microwave Corrosion Detector (MCD) is a handheld battery powered tool that operates much like an electronic stud finder. As the operator passes the MCD over a painted surface (organic coating) under which corrosion is present its display lights up to indicate the severity of the corrosion detected. The system also provides Geiger counter-like chip feedback to the operator through an earphone jack. A serial connection provides PC recording and analysis capabilities for corrosion trend monitoring. MCD outputs include: 1- a corrosion severity indicator and 2- the distance to bare metal from atop the coating. The principle of microwave detection is based: 1- on the dielectric change or 2-loss of energy from the reflected surfaces. The MCD is a self-contained, handheld NDT system
  • 17. Figure 9– Hand held MCD for corrosion detection under coatings
  • 18. Figure 10 - The schematic of microwave incident and reflected signals from atop the coating. The MCD senses these changes by comparing the incident and reflected microwave signals as they pass through the coating (paint) system and reflect off the aircraft’s metal substrate (see Figure 10).
  • 19. The MCD is powered by three internal AA batteries and can operate for up to 10 hours. It has a serial port to facilitate interconnection with a PDA, laptop, or PC for data recording and advanced real time displays. Both onboard and laptop supporting software can be customized for a wide variety of inspection scenarios. For corrosion under paints, the MCD is placed on the surface and moved by sliding for some reasonable length and then moved up or down to cover a specific area and storing the information. The reflected energy spectra can be stored in the computer during scanning for a reference and quantification. The results shown in Figure 11 were obtained by scanning over laths of corrosion on aluminum 7075-T6 plates that had undergone salt fog exposure. Figure 11- Dual mode laptop display of corrosion severity and damage on a 0.007 in thick painted Al 7075-T6 metal surface.
  • 20. Currently, a broad variety of corrosion detection and monitoring devices are available. The list shown below is a summary of them, starting from visual/optical type to those involving ultrasonics, microwave, thermal to chemical and electrochemical as detection methods and mechanisms. Visual/Optical Inspection – a sentry method using fiber optics (boroscope)  D-Sight, Edge of Light CCD (Charge Coupled Devices) video scanners and image analyzers  Guided Wave Ultrasonics and Ultrasound Imaging Acoustic Methods – using surface acoustic wave (SAW) device  Multifrequency Eddy Current Radiography - Neutron, Digital and X-Rays (low level - source)ϒ  Microwave Scanner, Dielectrometer  Thermal and Infrared Imaging (IR), Tomography Magneto-optic Eddy Current Imaging  Magnetic Particles, Magnetometer, SQUID, Magnetic Flux Electrical Methods – probes measuring resistance or potential change  Electrochemical Methods – using sensors that measure galvanic current, potential, resistance, and electrochemical impedance and noise Chemical Sensors - fluorescence and redox indicators, liquid penetrant, light obscurance, holographic interferometry  Other Miscellaneous Techniques - coulometry, calorimetry, etc.
  • 21. CONCLUSIONSCONCLUSIONS The sensor systems described in this paper perform two distinct functions: 1- measure corrosive nature of the environment present and 2- monitor the corrosion damage in hidden areas of aircraft and under coatings.
  • 22. REFERENCES 1. “Opportunities to Reduce Corrosion Costs and Increase Readiness”, Report to Congressional Committee, US General Accounting Office Report GAO-03-753, July 2003. 2. V.S. Agarwala and S. Ahmad, “Corrosion Detection and Monitoring – A Review”, CORROSION/2000, Paper No.271, 2000, NACE International, Houston, TX. 3. V.S. Agarwala, “Sensors for Monitoring Aircraft Corrosion Health”, Proceedings of 14th International Corrosion Congress, Paper No. 245.1, Sept. 27, 1999, Cape Town, South Africa; “In- Situ Corrosivity Monitoring of Military Hardware”, CORROSION/1996, Paper No. 632, 1996, NACE International, Houston, TX. 4. J.L. Rose, L.E. Soley, Tom Hay and V.S. Agarwala, “Ultrasonic Guided Waves for Hidden Corrosion Detection in Naval Aircraft”, CORROSION/2000, Paper No. 267, 2000, NACE International, Houston, TX. 5. Ignacio Perez and Paul Kulowitch, “Thermography Characterization of Corrosion Damage”, CORROSION/2000, Paper No. 290, 2000, NACE International, Houston, TX. 6. M. Twomey, “Inspection Techniques for Detecting Corrosion Under Insulation”, Material Evaluation, Vol. 55,129-33, 1997. 7. Neil Goldfine, “Enhancements in MWM-Array Hidden Corrosion Imaging”, Proceedings of 2003 Tri-Service Corrosion Conference, Las Vegas, NV, Session XVII, November 2003, Naval Air Systems Command, Patuxent River, MD. 8. Alan Bray, H. Stretz and S.C. Buckner, “Coating Effects in Microwave NDE in the Detection of Corrosion for Aircraft Application”, CORROSION/2000, Paper No. 268, 2000, NACE International, Houston, TX; “Microwave NDE Tool Development and Beta Testing”, Proceedings of 2003 Tri- Service Conference, Las Vegas, NV, Session XIII, November 2003, Naval Air Systems Command, Patuxent River, MD. 9. G.D. Davis, C.M. Dacres and L.A. Krebs, “EIS-Based In-Situ Sensors for the Early Detection of Coatings Degradation and Substrate Corrosion” CORROSION/2000, Paper No. 275, 2000, NACE International, Houston, TX. 10. J.N. Schoess, “Smart Fastener for KC-135 Structural Integrity Monitoring”, 1997 SPIE Smart Structures and Materials Conference, March 1, 1997. 11. Anna A. Panova, P. Pantano and D.R. Walt, “In-Situ Florescence Imaging of Localized Corrosion with a Ph Sensitive Imaging Fiber”, Analytical Chemistry, 69, 1635-1641, 1997. 12. R. Wood and R. Waldrop, “Infrared Thermal Imaging as a Tool for the Characterization of Corrosion”, Proceedings of 2003 Tri-Service Corrosion Conference, Las Vegas, NV, Session XVII, November 2003, Naval Air Systems Command, Patuxent River, MD. 13. D. Dixon, S. J. Harris, J.E. Cole, B.R.W. Hinton, et.al. “A Corrosion Prediction Model and Corrosion Sensor for Corrosion Management”, Proceedings of 2003 Tri-Service Corrosion Conference, Las Vegas, NV, Session F, November 2003, Naval Air Systems Command, Patuxent River, MD.
  • 23. hank you for your attentiohank you for your attentio May 2012 Erfan Zaker Esfahani