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A novel method to specify pattern recognition of actuators for stress reduction based on Particle swarm optimization method

机译:基于粒子群优化方法的执行器模式识别方法

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This paper is focused on stiffness ratio effect and a new method to specify the best pattern of piezoelectric patches placement around a hole in a plate under tension to reduce the stress concentration factor. To investigate the stiffness ratio effect, some different values greater and less than unity are considered. Then a python code is developed by using particle swarm optimization algorithm to specify the best locations of piezoelectric actuators around the hole for each stiffness ratio. The results show that, there is a line called "reference line" for each plate with a hole under tension, which can guide the location of actuator patches in plate to have the maximum stress concentration reduction. The reference line also specifies that actuators should be located horizontally or vertically. This reference line is located at an angle of about 65 degrees from the stress line in plate. Finally two experimental tests for two different locations of the patches with various voltages are carried out for validation of the results.
机译:本文着重于刚度比效应和一种新方法,该方法可指定在张力下减小孔中应力集中系数的最佳方式,将压电贴片放置在孔中。为了研究刚度比的影响,考虑了一些大于和小于1的不同值。然后,通过使用粒子群优化算法来开发python代码,以针对每个刚度比指定孔周围压电致动器的最佳位置。结果表明,每块板都有一条称为“参考线”的线,该板上有一个受拉孔,该线可以引导执行器补片在板上的位置,以最大程度地降低应力集中。参考线还指定了执行器应水平或垂直放置。该参考线与板中的应力线成约65度角。最后,针对具有不同电压的贴片的两个不同位置进行了两次实验测试,以验证结果。

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