Evaluation of axis straightness error in the machining of hole and shaft parts based on improved exponential distribution optimizer

Abstract

The straightness error of hole and shaft parts is one of the important parameters to reflect machining quality. The modeling process of traditional mathematical methods is complex, and the solution precision is not high. The intelligent optimization algorithm has significant advantages in solving this kind of problem. It can depend on random operators jumping out of local optima and does not need to calculate a large gradient information. Therefore, this paper proposes an improved exponential distribution optimization (IEDO) algorithm to achieve the minimum zone evaluation of straightness error. Firstly, the mathematical model of minimum zone method for axis straightness evaluation is established as the objective function. Secondly, the principle of the basic exponential distribution optimization (EDO) algorithm is described, and the exponential distribution optimizer is improved in three aspects: in the initialization, the interval shortening strategy is introduced to solve the problem of uneven initial population distribution; the adaptive switch probability is proposed to replace the constant value (0.5) to balance the ability of global exploration and local exploitation; a guidance strategy based on weight is proposed to guide the search process to reach the global optimal quickly. Then, nine typical benchmark functions are utilized to test the performance of the improved algorithm, which reveals satisfactory results. Finally, IEDO successfully applies to evaluation of axis straightness error with good accuracy.