Abstracts Book - IMRC 2018

• SE4-O025
CORROSION MEASUREMENT ON REINFORCED STEEL CONCRETE
AFTER EXPOSURE TO MARINE ENVIRONMENT BY
ELECTROCHEMICAL NOISE TECHNIQUE WITH ARTIFICIAL
INTELIGENCE
Guillermo Sosa Von Putlitz 1,2 , Ricardo Orozco Cruz 2 , Ricardo Galvan Martinez 2 , Hector Herrera
Hernandez 1 , Heriberto Casarruvias Vargas 1
1 Universidad Autónoma del Estado de México, Ing. Industrial, Mexico. 2 Universidad
Veracruzana, Instituto de Ingeniería, Mexico.
One of the most important effects of corrosion in concrete structures is the
reduction of the mechanical properties of steel-reinforcement. This is why
structural steels with corrosion resistance characteristics are commonly used to
extend the service life of the concrete structure, since it is not appropriate to
have a structure that only satisfies characteristics of mechanical resistance if a
suitable durability is not guaranteed. The ability to evaluate and control the
phenomena of electrochemical corrosion by sophisticated techniques remains
a research topic of great interest at worldwide level.
So, in this research work is intended to evaluate the electrochemical behavior of
the reinforcing steel embedded in concrete by using the electrochemical noise
EN technique with artificial intelligence AI theory. To carry out the
electrochemical evaluation, specimens of reinforced concrete were
manufactured with standard steel rods and different c/w ratio, and exposing in
a tropical marine atmosphere for a several time. EN is performed using
stochastic oscillation measurements of the corrosion potential E corr and current
I of two identical working electrodes with respect to a reference electrode. In
this type of technique plots of I and E vs. time are obtained. The EN data will be
analyzed using statistical and mathematical methods such as variance, standard
deviation, rapid Fourier transform (FFT), Wavelet transform (WT) and also a
neuronal network has been obtained to predict the corrosion damage on
reinforced-steel concrete.
Keywords: Steels, Electrochemical noise, Corrosion
Presenting authors email: hherrerah@uaemex.mx