The Experts below are selected from a list of 42 Experts worldwide ranked by ideXlab platform
Masatoshi Saitou - One of the best experts on this subject based on the ideXlab platform.
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scaling approach to galvanic current of stainless steel silver atmospheric Corrosion Monitor
Journal of The Electrochemical Society, 2000Co-Authors: Masatoshi SaitouAbstract:The galvanic current of stainless steel/silver atmospheric Corrosion Monitors exposed to the atmosphere for 4 months are analyzed to investigate the scaling behavior of Corrosion. The time series of the galvanic current indicate that the galvanic current has a scaling property; a scaling relation predicted by the scaling theory is consistent with the experimental results of the stainless steel/silver atmospheric Corrosion Monitor and the Hurst coefficient representing the effect of long memory is related to the type of Corrosion.
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fractal behavior of galvanic current of dual electrode type of atmospheric Corrosion Monitor
Journal of Chemical Physics, 1999Co-Authors: Masatoshi Saitou, W Oshikawa, S Itomura, S TsuzikawaAbstract:Eleven-month series of the galvanic current of dual electrode type devices exposed to the atmosphere are analyzed to make clear the fractal behavior of Corrosion. The result indicates that a relation predicted by the scaling theory is strictly consistent with the experimental result and the fractal behavior of Corrosion is insensitive to the local details.
Lizhe Shao - One of the best experts on this subject based on the ideXlab platform.
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data mining to online galvanic current of zinc copper internet atmospheric Corrosion Monitor
Corrosion Science, 2018Co-Authors: Yana Shi, Dawei Zhang, Xingyu Zhou, Tao Yang, Yuanjie Zhi, Zibo Pei, Lizhe ShaoAbstract:Abstract The galvanic current of a zinc/copper atmospheric Corrosion Monitor exposed to outdoor conditions is analysed to evaluate the corrosivity of the atmospheric environment. It is essential to develop effective and efficient models for the Monitored Corrosion current in order to uncover the underlying mechanism of the Corrosion process. In this paper, we propose a new variable, the Corrosion index, to quantify the corrosivity of the atmospheric environment. The time series of galvanic current is treated statistically to predict the Corrosion index via a hidden Markov model. The prediction model performs favourably on the online Corrosion data in terms of efficiency and accuracy.
Chanhee Park - One of the best experts on this subject based on the ideXlab platform.
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a method for estimating time dependent Corrosion depth of carbon and weathering steel using an atmospheric Corrosion Monitor sensor
Sensors, 2019Co-Authors: Youngsoo Jeong, Intae Kim, Seokhyeo Jeo, Chanhee ParkAbstract: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.
Liming Wang - One of the best experts on this subject based on the ideXlab platform.
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Corrosion measurement of the atmospheric environment using galvanic cell sensors
Sensors, 2019Co-Authors: Daiming Yang, Liming WangAbstract:An atmospheric Corrosion Monitor (ACM) is an instrument used to track the Corrosion status of materials. In this paper, a galvanic cell sensor with a simple structure, flexible parameters, and low cost was proposed for constructing a novel ACM, which consisted of three layers: the upper layer was gold, used as the cathode; the lower layer was corroded metal, used as the anode; and the middle layer was epoxy resin, used to separate the cathode and anode. Typically, the anode and epoxy resin were hollowed out, and the hollow parts were filled with electrolyte when it was wet to form a corrosive galvanic cell. Specifically, the Corrosion rate was obtained by measuring the short circuit current of the cell. The sensor was made of a printed circuit board (PCB) or flexible printed circuit (FPC) and a metal coupon, which allowed for early control of the electrical parameters (including sensitivity and capacity) and could be combined with various metals. Additionally, the sensor feasibility was studied in water droplet experiments, during which the corrosive current changed with the electrolyte evaporation. The sensor practicability was also verified in a salt spray test, and the electric charge was compared using the thickness loss of bare coupons. A contrast test was also conducted for the corrosivity of different sensors made of aluminum, iron and copper.
Yana Shi - One of the best experts on this subject based on the ideXlab platform.
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data mining to online galvanic current of zinc copper internet atmospheric Corrosion Monitor
Corrosion Science, 2018Co-Authors: Yana Shi, Dawei Zhang, Xingyu Zhou, Tao Yang, Yuanjie Zhi, Zibo Pei, Lizhe ShaoAbstract:Abstract The galvanic current of a zinc/copper atmospheric Corrosion Monitor exposed to outdoor conditions is analysed to evaluate the corrosivity of the atmospheric environment. It is essential to develop effective and efficient models for the Monitored Corrosion current in order to uncover the underlying mechanism of the Corrosion process. In this paper, we propose a new variable, the Corrosion index, to quantify the corrosivity of the atmospheric environment. The time series of galvanic current is treated statistically to predict the Corrosion index via a hidden Markov model. The prediction model performs favourably on the online Corrosion data in terms of efficiency and accuracy.
