Imaging and Information Processing of Pitting-Corroded Aluminum Alloy Panels with Surface Metrology Methods

Honglei Li, Margaret R. Garvan, Jiaming Li, Javier Echauz, Douglas Brown, and George J. Vachtsevanos
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Full Paper
phmc_14_032.pdf1.09 MBSeptember 19, 2014 - 8:41pm

It has been established that corrosion is one of the most important factors causing structural deterioration, loss of metal, and ultimately decrease of product performance and reliability. Corrosion monitoring, accurate detection and interpretation are recognized as key enabling technologies to reduce the impact of corrosion on the integrity of critical aircraft and industrial assets. Interest in corrosion measurement covers a broad spectrum of technical approaches including acoustic, electrical and chemical methods. Surface metrology is an alternative approach used to measure corrosive rate and material loss by obtaining surface topography measurement at micrometer levels. This paper reports results from an experimental investigation of pitting corrosion detection and interpretation on aluminum alloy panels using 3D surface metrology methods, image processing and data mining techniques. Sample panels of AA 7075-T6, an aluminum alloy commonly used in aircraft structures, were coated on one side with a corrosion-protection coating and assembled in a lap-joint configuration. Then, a series of accelerated corrosion testing of the lap-joint panels were performed in a cyclic corrosion chamber running ASTM G85-A5 salt fog test. Panel surface characterization was evaluated with laser microscopy and stylus-based profilometry to obtain global and local surface images/characterization. Promising imaging and surface features were extracted and compared between the uncoated and coated panel sides, as well as on the uncoated sides under different corrosion exposure times. In the evaluation process, image processing, information processing and other data mining techniques were utilized. Information processing involves the steps of feature or Condition Indicator extraction and selection. The latter step addresses the problem of selecting those features that are maximally correlated with the actual corrosion state, for the purpose of corrosion detection, localization, quantification and state estimation. The results, verified by mass loss data, confirmed the contention that pits at the panel surfaces formed as a result of electrochemical corrosion attack, and showed that deteriorating pitting corrosion attack correlates with increasing corrosion exposure times. This study is a first step in the process of understanding, assessing and responding to the pitting corrosion and ultimately preventing material failure to insure aircraft structural integrity.

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Submission Keywords: 
structural health monitoring
data mining
pitting corrosion
surface metrology
image processing
aluminum alloy
Submission Topic Areas: 
Structural health monitoring
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