Yield Characteristics Strengthening and Yield Strength Anti-Dispersion Identification Based on Bending Deformation

Abstract

The online derivation of material yield is important for consistency control of product quality. Compare with other deformation, bending deformation is more suitable for online identification. The transition portion of bending force stroke curve is related to the yield strength of material, but for a wide set of materials with different thickness and properties, its longer transition curve shows higher identification scattering. In this paper, the yield characteristics strengthening method and the new anti-dispersion identification method are studied to reduce the scattering. It is found that the yield characteristics are comprehensively affected by several factors. The higher yield strength, together with thinner thickness, can weaken the yield characteristics. The thicker material with wider die span can strengthen the yield characteristics. Window vector method (WV) and standardized fitting residual method (SFR) are proposed. Through the numerical study found that the yield load obtained by WV method shows a most accurate correlation with yield strength. A novel piecewise correlation equation is proposed and added a thickness variable to eliminate partial dispersion from varied thickness. Furthermore, this paper uses the experimental data to extract the generalization error of new correlation model fitted by yield loads from WV method, maximum error is below 12%. This method can improve the accuracy and efficiency of online ranking materials.