1. IN SITU CORROSION MONITORING AND ASSESSMENT WITH DIAGNOSTIC AND PROGNOSTIC CAPABILITIES FOR CONDITION-BASED MAINTENANCE   Dr. Bernard Laskowski, Analatom Incorporated Duane Darr, Analatom Incorporated

2. AN110 Data Acquisition (DAQ) Node
Micro-linear polarization resistance (µLPR) corrosion sensors provide direct real-time measurements of electrochemical activity for structural health monitoring (SHM) applications.
Utilizing established linear polarization resistance (LPR) technology, sensors output an identical corrosion rate for the metallic structure on which they are placed, as they are constructed from the same temper and alloy.
These ultrathin flexible sensors can be placed on bare metal surfaces and beneath coatings to allow fitting to virtually any surface.
µLPR Corrosion Sensor
AN110 Data Acquisition (DAQ) Node

3. Coating Integrity/Degradation
Corrosion Sensing beneath Coatings
Over time, protective coating systems degrade and defect sites form permitting micro-fluid electrolyte transport of corrosive species along the metal-coating boundary.
Resulting coating delamination increases diffusion rate, accelerating corrosion process over much larger area than defect size.
µLPR design allows installation beneath protective coatings, sealants, or insulation.
In situ monitoring of coating integrity gives early warning of coating degradation for preventive maintenance action in place of major repair.
Effective sensor radius, over time under coatings, can be 1-5 meters, depending on coating system’s physical characteristics.
Deep Space Deep Ocean I 2015

4. Illustration Prognostics
Experimental Pit Depth (Exp2) Evaluation of 7075-T6 Aluminum Alloy Lap Joint Panels
The computed pit-depth for each of the 24 µLPR sensors over a period of approximately 60 days is provided in Figure 8.
Fig 8. Actual and µLPR Corrosion Rate Sensor Data Computed Pit-depth Progression over Time

5. Projects - Aerospace
Flight Installations:
Two major carriers, commercial passenger revenue flights.
FAA approved SHM system for Sabreliner 40 business aircraft.
Air Force certified SHM system for C-130 military cargo aircraft.

6. Projects - Vehicles Fleet of trucks in Hawaii ravaged by corrosion
SHM systems fitted
Data collected:
corrosion rate (µLPR sensor)
Satellite imagery (Internet)
Weather station data (Internet)

7. Projects – Bridges
µLPR (Linear Polarization Resistance) Corrosion Sensor and
Corrosion Health Monitoring System (CHMS) DAQ
Federal Highway Administration report (FHWA-HRT ) detailing, in part, installation and performance of Analatom corrosion monitoring system on Manhattan Bridge states (p. 166):
In conclusion, this study demonstrated that it is possible to measure corrosion activity inside main cables of suspension bridges. The information provided by such a system can be used to make more reliable estimations of the safety factor and remaining service life of such important structural elements as well as to help bridge engineers in conducting more efficient and cost effective inspections. Because of the continuous advancements in sensor and NDT technologies, it is important to pay attention to any new developments that can help improve such a monitoring system.
Deep Space Deep Ocean I 2015

8. PETROCHEMICAL FIELD APPLICATION
Objective is to perform a field validation of the μLPR system for corrosion monitoring on the exterior surface of an underground test pipeline.
The μLPR sensors were installed on 6-inch diameter industry standard line pipe and the pipe reburied. An AN110-C commercial CHMS system was used to provide direct real-time measurements of corrosion rate activity for the pipeline under accelerated corrosion conditions.
The sensors were electrically isolated from the structure and coupons, but responded to corrosive conditions identically. In addition, relative humidity and temperature were monitored above ground.
The field test was to demonstrate that the µLPR corrosion rate sensor accurately measure structural mass losses.
Corrosion rates are dynamic variables that change orders of magnitude depending on the intensity of corrosive conditions. When corrosion rate data is converted to corrosion loss data by time integration, information concerning the indicated mass loss of the monitored structure over time, in this case coupons, is directly observable.
Cumulative sum of corrosion rate sensor measurements over time yields the indicated corrosion loss of structure, in this case low carbon line pipe steel.

9. PETROCHEMICAL FIELD RESULTS
Over the 13-month field test, both the pipe and the 8 coupons were under accelerated corrosion conditions.
Average pipe current density (77,000 µA/~5000 in2 effective external area = 15.4 µA/in2) was about ¼ the average coupon current density (395 µA/6.34 in2 = 62.3 µA/in2); therefore, the four corrosion sensors on the pipe should indicate a corrosion rate about one-fourth the four sensor bearing coupons’ corrosion rates.
Test Pipeline Corrosion Rate Sensor Mass Loss Data (4 on coupons, 4 on pipe; 13 months)

10. Projects - Facilities
In situ corrosion rate monitoring over time allows higher fidelity structural degradation information—especially in hard to access areas—and improved maintenance decision-making capability.
Roof installation on critical building
with corrosion issue due to location
in subtropical region.

11. Radar Mast: Monitoring Corrosion in Difficult To Access Areas
Projects - Maritime
Micro LPR Sensor-based Corrosion Monitoring System
Data Mining – Maintenance, Sensor, Route, Environmental Data
Maritime Technology Transfer
Increase efficiency and useful life of ship hull with continuous monitoring of the functioning of hull’s cathodic corrosion protection
747 Engine
Radar Mast: Monitoring Corrosion in Difficult To Access Areas
Ship Engine
Corrosion Ship Heat Exchanger

12. Summary
We present applications, results, and experimental validation of the corrosion monitoring / assessment system.
Experiments used standard ASTM G85-A5 and SAE J2334 cyclic corrosion testing. Sensor corrosion rates were compared against witness coupons.
Corrosion computed from sensors agreed with coupon mass loss to within a 95% confidence interval.
For aerospace alloys, pit-depth was computed from LPR data and compared to average pit-depths measured on AA 7075-T6 coupons, thus demonstrating sensor effectiveness for pit-depth measurement with prognostic application.
In funded research1 the µLPR system was utilized in validation of a model of residual and diffusion induced stresses on corrosion at the interface of coating and substrate.
In a long-term petrochemical application, monitoring buried steel line pipe, corrosion computed from sensors agreed with coupon mass losses to within 12-13%, demonstrating the utility of the μLPR system to measure corrosion activity under protective coatings in below ground environments.
1. Defence Science and Technology Laboratory, Ministry of Defence, and Bournemouth University