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99198 ELECTROCHEMICAL NOISE MEASUREMENTS OF SUSTAINED MICROBIALLY INFLUENCED PITTING CORROSION IN A LABORATORY FLOW LOOP SYSTEM

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Product Number: 51300-99198-SG
ISBN: 99198 1999 CP
Author: Daniel H. Pope, YUPOJ. Lin, James R. Frank, and Edward J. St.Martin
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Because of the chaotic nature of the corrosion process and the complexity of the electrochemical noise signals that are generated, there is no generally accepted method of measuring and interpreting these signals that allows the consistent detection and identification of sustained lcnlized pitting (SLP) as compared to general corrosion. We have reexamined electrochemical noise analysis (ENA) of localized corrosion using different hardware, signal collection, and signal processing designs than those used in conventional ENA techniques. The new data acquisition system was designed to identify and monitor the progress of SLP by analyzing the power spectral density (PSD) of the trend of the corrosion current noise level (CNL) and potential noise level (PNL). Each CNL and PNL data point was calculated from the rootmean- square value of the ac components of current and potential fluctuation signals, which were measured simultaneously during a short time period. The PSD analysis results consistently demonstrated that the trends of PNL and CNL contain information that can be used to differentiate between SLP and general corrosion mechanisms. The degree of linear slope in the low-frequency portion of the PSD analysis was correlated with the SLP process. Laboratory metal coupons as well as commercial corrosion probes were tested to ensure the reproducibility and consistency of the results. The on-line monitoring capability of this new ENA method was evaluated in a bench-scale flow-loop system, which simulated microbially influenced corrosion (MIC) activity. The conditions in the test flow-loop system were controlled by the addition of microbes and different substrates to favor accelerated corrosion. The ENA results demonstrated that this in-situ corrosion monitoring system could effectively identify SLP corrosion associated with MIC, compared to a more uniform general corrosion mechanism. A reduction in SLP activity could be clearly detected by the ENA monitoring system when a corrosion inhibitor was added into one of the test loops during the corrosion testing. Keywords: electrochemical noise, corrosion, microbially influenced corrosion (MIC), sensor, sustained localized pitting (SLP).
Because of the chaotic nature of the corrosion process and the complexity of the electrochemical noise signals that are generated, there is no generally accepted method of measuring and interpreting these signals that allows the consistent detection and identification of sustained lcnlized pitting (SLP) as compared to general corrosion. We have reexamined electrochemical noise analysis (ENA) of localized corrosion using different hardware, signal collection, and signal processing designs than those used in conventional ENA techniques. The new data acquisition system was designed to identify and monitor the progress of SLP by analyzing the power spectral density (PSD) of the trend of the corrosion current noise level (CNL) and potential noise level (PNL). Each CNL and PNL data point was calculated from the rootmean- square value of the ac components of current and potential fluctuation signals, which were measured simultaneously during a short time period. The PSD analysis results consistently demonstrated that the trends of PNL and CNL contain information that can be used to differentiate between SLP and general corrosion mechanisms. The degree of linear slope in the low-frequency portion of the PSD analysis was correlated with the SLP process. Laboratory metal coupons as well as commercial corrosion probes were tested to ensure the reproducibility and consistency of the results. The on-line monitoring capability of this new ENA method was evaluated in a bench-scale flow-loop system, which simulated microbially influenced corrosion (MIC) activity. The conditions in the test flow-loop system were controlled by the addition of microbes and different substrates to favor accelerated corrosion. The ENA results demonstrated that this in-situ corrosion monitoring system could effectively identify SLP corrosion associated with MIC, compared to a more uniform general corrosion mechanism. A reduction in SLP activity could be clearly detected by the ENA monitoring system when a corrosion inhibitor was added into one of the test loops during the corrosion testing. Keywords: electrochemical noise, corrosion, microbially influenced corrosion (MIC), sensor, sustained localized pitting (SLP).
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