Roundness error evaluating method based on gravitational acceleration cuckoo algorithm

Abstract

Disclosed is a roundness error evaluating method based on a gravitational acceleration cuckoo algorithm. Based on gravitational search, the characteristics of global optimal information can still be perceived without learning the change of external environmental factors. Cuckoo nests are endowed with different individual masses, and the cuckoo nests obey the law of gravitation in the optimizationprocess. Acceleration search is carried out on Levy flight random walk and preferential random walk in the cuckoo algorithm based on the gravity among optimization individuals to get the update locations of corresponding cuckoo parasitic nest individuals. Under the action of gravity, the global search ability and the local search ability of the cuckoo algorithm are balanced, the hysteresis phenomenon due to the fact that the algorithm gets into a local extreme point at the end of execution is avoided, and the global search efficiency and convergence precision of the algorithm are improved. Theroundness error E to be optimized can quickly tend to be a stable optimal value. The ideal centers Xmin(1) and Xmin(2) of two concentric circles are calculated, and thus, the area between the two concentric circles is the minimum.

Description

technical field [0001] The invention relates to the technical field of circular error assessment, and more particularly, to a circularity error assessment method based on the gravitational acceleration cuckoo algorithm. Background technique [0002] Roundness error evaluation is an important evaluation index in the machining process of rotary parts, and its accuracy directly affects the quality and service life of the machined workpiece. The classic methods for evaluating roundness error include least squares method, least circumscribed circle method, maximum inscribed circle method and minimum area circle method. The least squares theory is relatively mature, but it involves nonlinear operations, and the algorithm complexity is high. At the same time, the evaluation result has a large error, and the roundness error evaluation result of the minimum condition cannot be satisfied. The minimum circumscribed circle method is to take the minimum circumscribed circle of the actu...

AI Technical Summary

Problems solved by technology

Taken together, although this type of improved algorithm improves the comprehensive performance in the search process, such as population diversity, convergence accuracy, etc., the cost is to increase the number of function evaluations and the complexity of the algorithm

When dealing with high-dimensional optimization problems, especially multimodal functions, ridge-peak functions, and singular functions, the adaptive adjustment ability of the algorithm is poor, resulting in unsatisfactory optimization results

At the same time, the existing improved algorithms usually combine the two algorithms mechanically, without digging into the internal mechanism of the population optimization process, and the algorithm execution efficiency is low

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