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Advanced Modeling and Simulation in Engineering Sciences

Table 2 Data included in the analysis

From: Parasitic resistance as a predictor of faulty anodes in electro galvanizing: a comparison of machine learning, physical and hybrid models

Variable name Sensor/measurement description Use
Fe concentration in electrolyte ICP-OES Predictive
pH of the electrolyte Potentiometric (pH sensor) Predictive
Na concentration in electrolyte ICP-OES Predictive
Zn concentration in electrolyte ICP-OES Predictive
Electrolyte temperature Pt-100 Predictive
Width of steel strip Tactile width measurement Predictive
Thickness of steel strip Radiometric Predictive
Specific resistance Current–Voltage determination (4-point method) Predictive
Rectifier current Potential drop at shunt Predictive
Rectifier voltage Potential Target
  1. The variables are divided into three groups: electrolyte parameters, strip parameters, current characteristics. Out of these, nine parameters will be used as predictive variables
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