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Related Experiment Video

Updated: May 11, 2026

Potentiodynamic Corrosion Testing

Potentiodynamic Corrosion Testing

Published on: September 4, 2016

LabVIEW 2010 Computer Vision Platform Based Virtual Instrument and Its Application for Pitting Corrosion Study.

Rogelio Ramos¹, Roumen Zlatev, Benjamin Valdez

¹Engineering Institute, Autonomous University of Baja California, Boulevard Benito Juarez S/N, 21280 Mexicali, BCN, Mexico.

Journal of Analytical Methods in Chemistry

|May 22, 2013

Summary

A new virtual instrumentation system, the Localized Corrosion Image Analyzer (LCIA), automatically detects and analyzes corrosion pits on large specimens. This system enhances corrosion analysis by integrating with Scanning Vibrating Electrode Technique (SVET) for targeted investigations.

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Area of Science:

Materials Science
Electrochemistry
Instrumentation Engineering

Background:

Localized corrosion, particularly pitting, is a significant challenge in material degradation.
Accurate and efficient detection of corrosion pits is crucial for material lifespan assessment.
Current methods for pit analysis can be time-consuming and subjective.

Purpose of the Study:

To develop a virtual instrumentation (VI) system for automated, objective, and rapid analysis of localized corrosion pits.
To integrate digital microscopy and image analysis for precise pit characterization.
To streamline the subsequent electrochemical analysis using Scanning Vibrating Electrode Technique (SVET).

Main Methods:

Development of a LabVIEW-based virtual instrumentation system, the Localized Corrosion Image Analyzer (LCIA).
Synchronized control of digital microscope image acquisition and automated image analysis.
Application of binary large objects (blobs) analysis for pit quantification (number, area, traverse length, density).
Generation of a map file with pit coordinates for targeted SVET analysis.

Main Results:

The LCIA system enables rapid, automatic, and error-free determination of pit numbers on large corroded specimens.
The system accurately quantifies pit area, traverse length, and density.
Generated map files facilitate a significantly faster, one-pass SVET analysis by focusing only on probable pit locations.

Conclusions:

The developed VI system (LCIA) offers a robust solution for objective and efficient localized corrosion pit analysis.
Integration with SVET significantly reduces analysis time by enabling targeted electrochemical measurements.
This approach enhances the speed and accuracy of corrosion assessment on metallic specimens.