Identification of eccentricity of a motorized spindle-tool system with random parameters

Identification of eccentricity of a motorized spindle-tool system with random parameters
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具有随机参数的电动主轴刀具系统的偏心率识别

DOI:
10.5194/ms-12-715-2021
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发表时间:
2021-07
期刊:
Mechanical sicences
影响因子:
--
通讯作者:
Dan Feng
Dan Feng
中科院分区:
其他
文献类型:
--
作者:
Wengui Mao;Qingqing Tang;Dan Feng

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抽象的。为了提高识别的效率 参数采用极大似然法,避免了对初值的敏感性 提出了一种将微遗传算法与改进的遗传算法相结合的方法 为了识别主轴刀具的偏心,提出了退刀方法 具有随机输入和输出参数的系统,其服从 一定的概率分布。无先验信息的偏心率 是通过迭代过程确定的。初始值从 零,间隔由超前和 退避法。然后在对应的区间内搜索最优值, 利用微遗传算法。在每个位置的初始值和间隔 改变迭代以确保快速稳定的收敛。最终,一个 具有三种随机偏差的数值算例验证了该方法的有效性 验证了该方法的可行性和有效性。
Abstract. In order to improve the efficiency of identifying parameters using the maximum likelihood method and to avoid the sensitivity of initial values, a proposed method that combines the micro-genetic algorithm with the advance and retreat method is presented in order to identify the eccentricity of the spindle-tool system with random input and output parameters, which obey a certain probability distribution. Eccentricity without prior information is determined through an iterative procedure. The initial value starts from zero, and the interval is determined by the advance and retreat method. Then, the optimal value is searched in the corresponding interval, utilizing the micro-genetic algorithm. The initial value and interval at each of iterations are changed to ensure a fast and stable convergence. Eventually, a numerical example with three kinds of random deviations verifies the feasibility and validity of the proposed method.
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发表时间: 2001-12
影响因子: 7.2
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