Prediction of aluminium content in a metal using SPSS based linear regression analysis.

Abstract

Abstract In aluminium industry, it is very important to know the type or grade of aluminium metals and its composition present within the aluminium metals using non-destructive testing (NDT). A method is required which is unique and help to know the type of the aluminium material in order to characterize the aluminium samples. Ultrasonic testing is one of the best NDT techniques which are used for characterization of properties of the material. Recently it is observed that ultrasonic testing parameters are significantly depends on microstructural or mechanical properties of materials and the parameters are affected by change in structural properties of materials. To extract the more information from ultrasonic signals, signal processing techniques are the best tools which are using now days. In this paper new technique is introduced to obtain the concentration of aluminium in aluminium material in terms of ultrasonic parameters hardness, velocity, attenuation & modulus of elasticity by using linear regression analysis using Statistical package for Social Sciences i.e., SPSS statistics. The regression equation which is obtained to calculate aluminium percentage is compared with the experimental value of aluminium percentage in the materials. In the present paper the accuracy or reliability of the mathematical model has been estimated. To estimate the aluminium percentage in aluminium this type of model will be very helpful.