The Population Predicting Based on the Curve Fitting Least Square Method

He, Lin; Jin, Zhengguo

doi:10.2991/amcce-15.2015.258

Cited by 2 publications

(1 citation statement)

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“…The least square method can easily obtain unknown data and minimize the sum of squares of errors between the obtained data and the actual data. When used as an interpolation method, the least square method can also be used for curve fitting [37]. The theory of the least square method is simple, and the calculation is small.…”

Section: Numerical Analysis Methodsmentioning

confidence: 99%

Research on Structural Parameter Optimization and Springback Compensation Methods of a Steel Bar Hoop Bending Machine

Wei,

Ren,

Zhou

et al. 2023

Applied Sciences

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After being processed into a certain shape by a stirrup bending machine, steel bars are used as the skeleton of reinforced concrete in construction. The accuracy of their bending directly affects the bearing capacity of reinforced concrete. In order to improve the accuracy of the springback angle of steel bars after bending, this paper focuses on optimizing the structural parameters of the steel bar bending machine and controlling the springback angle of steel bars. The influence of the support shaft diameter, bending crankshaft diameter, and bending crankshaft radius on the springback angle of steel bars is analyzed using ANSYS explicit dynamic simulation and experimental analysis. By combining orthogonal experimental methods, the bending structural parameters were optimized, including a support shaft diameter of 20 mm, a crankshaft bending diameter of 40 mm, and a crankshaft bending radius of 80 mm. This can effectively reduce the springback angle of the steel bars and improve the accuracy of the bending angle after bending. In addition, in order to improve the control accuracy of the steel bar springback angle, a cubic spline interpolation method was proposed, and the collected steel bar springback angle data were fitted using Matlab. At the same time, comparisons were made between the least squares method, polynomial interpolation method, and cubic spline interpolation method. The results show that the compensation formula obtained by using the cubic spline interpolation method can effectively improve the control accuracy of the steel bar bending springback angle.

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Section: Numerical Analysis Methodsmentioning

confidence: 99%