Tilt measurement and compensation algorithm for holographic data storage with optimized quadratic windows

Abstract In holographic data storage, tilt is one of the critical disturbances. There are two types of tilt: tangential and radial. In real systems, tangential and radial tilt occur simultaneously. Thus, it is difficult to measure and compensate for tilt. In this study, using a quadratic window, which compares the intensity of a certain area, a tilt error signal was generated and compensated for with the proposed algorithm. The compensated image obtained satisfied a 0.3 dB tolerance.</jats:p

Modeling of slag foaming height of electric arc furnace using stepwise regression analysis

Slag foaming directly affects the productivity and quality of steel during the electric arc furnace (EAF) process. Therefore, the slag foaming height needs to be monitored in real-time. However, direct measurement of the slag foaming height is difficult to achieve because the inside of the EAF consists of harsh environments, i.e., high temperature and the presence of gas and dust. A stepwise regression model of the slag foaming height was created using sensor data from the EAF. A total of 272 operational data sets from the EAF process were used to develop and validate the regression model. This data came from 140ton DC-EAF of Dongkuk Steel in Pohang, Korea. We randomly selected 80% of the data for developing the regression model; the remaining 20% of data were used for model validation. The model was validated using the validation benchmark coefficient of determination (R2) and correlation coefficients. As a result, the important variables of slag foaming were statistically selected a priori. Using the regression model, the slag foaming height can be predicted without additional sensors. Based on the developed model, the effects of oxygen injection and carbon injection on the slag foaming height of EAF were predicted and are discussed herein.</jats:p