Present: Erfan Zaker EsfahaniEmail: aref_z_e@yahoo.comNumber: ----------------Lecturer: Dr. saatchiUniversity: najaf abadNumber of student: 890914688Course: Corrosion in Natural Environments

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outlineoutline

IntroductiIntroductionon

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 goodreliability 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 compositedisbond. 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.

CCCpretreated

couponsandwich

test coupon:

inside view.

Cr(III)pretreated sandwich

test coupon: insideview.

ICS Data GatheringTransponder (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

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Cou

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CurrentvsTime6/19/02

1.000E-08

1.000E-07

1.000E-060.0 24.0 48.0 72.0 96.0 120.0

Time(Hrs)

Sensor90 Sensor43

CoulombsvsTime6/19/02

0.05000000

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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 #8Equipment Rack E-1

Sensor #6Aft MainRing Fitting

Sensor #5Forward Main

Sensor #4Sensor #3HorizontalStab Skin

F.S. 323

Sensor #1Outboard Nacelle

Sensor #7Heat 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.

Corrosion Corrosion MonitoringMonitoringThe 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 clothCathode

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

1.41.21

0.8

0.6

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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.

104.5109.0113.6

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50.054.559.163.668.172.777.281.886.390.995.499.9

0.04.69.1

Time (Days)

Cou

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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

Cou

lom

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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 DetectorMicrowave 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 and2- 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 inthick 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 ImagingAcoustic Methods – using surface acoustic wave (SAW) device Multifrequency Eddy CurrentRadiography - Neutron, Digital and X-Rays (low level ϒ - source) Microwave Scanner, Dielectrometer Thermal and Infrared Imaging (IR), TomographyMagneto-optic Eddy Current Imaging Magnetic Particles, Magnetometer, SQUID, Magnetic FluxElectrical Methods – probes measuring resistance or potential change Electrochemical Methods – using sensors that measure galvanic current, potential, resistance, and electrochemical impedance and noiseChemical 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.

REFERENCES1. “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 14 th 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, PatuxentRiver, MD.

Thank you for your attentionThank you for your attentionMay 2012

Erfan Zaker

Esfahani