Technical Note:A Novel Corrosion Monitor Based on the Faradaic Rectification Technique

CORROSION ◽  
1983 ◽  
Vol 39 (7) ◽  
pp. 293-293 ◽  
Author(s):  
J. S. Gill ◽  
L. M. Callow ◽  
G. A. M. Sussex ◽  
J. D. Scantlebury
Keyword(s):  
Corrosion Monitor ◽  
Faradaic Rectification

scholarly journals Application of An Electrical Resistance Sensor-Based Automated Corrosion Monitor in the Study of Atmospheric Corrosion

Materials ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1065 ◽  
Author(s):  
Zhuolin Li ◽  
Dongmei Fu ◽  
Ying Li ◽  
Gaoyuan Wang ◽  
Jintao Meng ◽  
...  
Keyword(s):  
Electrical Resistance ◽  
Atmospheric Corrosion ◽  
Continuous Measurement ◽  
Atmospheric Environment ◽  
Corrosion Monitoring ◽  
Metallic Materials ◽  
Actual Environment ◽  
The Internet Of Things ◽  
Corrosion Monitor ◽  
Corrosion Data

An automated corrosion monitor, named the Internet of Things atmospheric corrosion monitor (IoT ACM) has been developed. IoT ACM is based on electrical resistance sensor and enables accurate and continuous measurement of corrosion data of metallic materials. The objective of this research is to study the characteristics of atmospheric corrosion by analyzing the acquired corrosion data from IoT ACM. Employing data processing and data analysis methods to research the acquired corrosion data of steel, the atmospheric corrosion characteristics implied in the corrosion data can be discovered. Comparing the experiment results with the phenomenon of previous laboratory experiment and conclusions of previously published reports, the research results are tested and verified. The experiment results show that the change regulation of atmospheric corrosion data in the actual environment is reasonable and normal. The variation of corrosion depth is obviously influenced by relative humidity, temperature and part of air pollutants. It can be concluded that IoT ACM can be well applied to the conditions of atmospheric corrosion monitoring of metallic materials and the study of atmospheric corrosion by applying IoT ACM is effective and instructive under an actual atmospheric environment.

scholarly journals A Method for Estimating Time-Dependent Corrosion Depth of Carbon and Weathering Steel Using an Atmospheric Corrosion Monitor Sensor

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1416 ◽  
Author(s):  
Jin-Hee Ahn ◽  
Young-Soo Jeong ◽  
In-Tae Kim ◽  
Seok-Hyeon Jeon ◽  
Chan-Hee Park
Keyword(s):  
Carbon Steel ◽  
Estimation Method ◽  
Depth Estimation ◽  
Corrosion Current ◽  
Time Dependent ◽  
Weathering Steel ◽  
Corrosion Depth ◽  
The Mean ◽  
The Relationship ◽  
Corrosion Monitor

In this study, a time-dependent corrosion depth estimation method using atmospheric corrosion monitor (ACM) sensor data to evaluate time-dependent corrosion behaviors is proposed. For the time-dependent corrosion depth estimation of uncoated carbon steel and weathering steel, acceleration corrosion tests were conducted in salt-spray corrosion environments and evaluated with a corrosion damage estimation method using ACM sensing data and corrosion loss data of the tested steel specimens. To estimate the time-dependent corrosion depth using corrosion current by an ACM sensor, the relationship between the mean corrosion depth calculated from the weight loss method and the corrosion current was evaluated. The mean corrosion depth was estimated by calculating the corrosion current and evaluating the relationship between the mean corrosion depth and corrosion current during the expected period. From the test and estimation results, the corrosion current demonstrated a good linear correlation with the mean corrosion depth of carbon steel and weathering. The calculated mean corrosion depth is nearly the same as that of the tested specimen, which can be well used to estimate corrosion rate for the uncoated carbon steel and weathering steel.

scholarly journals Faradaic rectification: An amended treatment—II. Experimental verification

1969 ◽  
Vol 14 (12) ◽  
pp. 1183-1192 ◽  
Author(s):  
R. de Leeuwe ◽  
M. Sluyters-Rehbach ◽  
J.H. Sluyters
Keyword(s):  
Experimental Verification ◽  
Faradaic Rectification
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