Quality monitoring method of strip hot-dip galvanizing based on partial least squares regression

A quality monitoring method for strip hot-dip galvanizing based on partial least square regression was proposed. Taking the quality monitoring of mechanical properties and zinc coating mass in strip hot-dip galvanizing as the investigated subject, a regression model between process parameters and quality results was constructed through partial least square method. With the regression model, the capability of production process control was analyzed and a production quality prediction method was presented, Real field data from strip hot-dip galvanizing production in Angang Steel Company Limited were used for validation, The results show that partial least square regression has a better predicting precision than traditional multiple linear regression, and that the zinc coating mass prediction model based on partial least square regression has a relative prediction error of 5.93%.