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Dynamic characteristic analysis of cracked cantilever beams under different crack types

机译:不同裂缝类型下裂纹悬臂梁的动态特性分析

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In order to simulate the complicated dynamic phenomena of cantilever beam structures with different crack types and levels in the engineering machinery, three types of cracks are assumed, i.e., non-penetrating parabolic crack (NPPC), penetrating trapezoid crack (PTC) and uniform-penetrating crack (UPC). Based on ANSYS software, mixed elements combining beam elements and solid elements are adopted to establish the finite element (FE) models of cracked cantilever beams where the crack levels are evaluated by introducing the area damage factor, i.e., the ratio of the damage area to the cross-sectional area. Then vibration responses and crack level identification of the system under three cases of crack severity are discussed by the spectrum cascades, acceleration-velocity and velocity-displacement phase portraits, and contact pressure nephograms. The results show that the magnitudes of constant components in the spectra increase with the increase of crack severity. Lateral velocity-displacement phase portraits, perpendicular to the excitation direction, are more sensitive to the appearance of the small crack than acceleration-velocity phase portraits in the excitation direction, and the combination of the two phase portraits can be used to identify the crack severity. The crack breathing effects can be evaluated using contact pressures distributions, and local contact phenomenon can be observed during the positive half circle of the excitation period under the larger crack conditions. (C) 2017 Elsevier Ltd. All rights reserved.
机译:为了模拟具有不同裂缝类型和工程机械水平的悬臂梁结构的复杂动态现象,假设三种类型的裂缝,即非穿透抛物线裂缝(NPPC),穿透梯形裂纹(PTC)和均匀 - 穿透裂缝(UPC)。基于ANSYS软件,采用混合元件组合光束元件和固体元件来建立裂纹悬臂梁的有限元(FE)模型,通过引入面积损伤因子,即损伤区域的比率来评估裂缝水平横截面积。然后通过光谱级联,加速 - 速度和速度 - 位移相位肖像讨论了三种裂纹严重程度下系统的振动响应和裂纹水平识别,并接触压力浊音。结果表明,光谱中恒定组分的幅度随着裂缝严重程度的增加而增加。垂直于激发方向的横向速度 - 位移相位肖像对小裂缝的外观比激发方向上的加速 - 速度相位肖像更敏感,并且可以使用两相肖像的组合来识别裂缝严重程度。可以使用接触压力分布来评估裂纹呼吸效果,并且在较大的裂纹条件下激发时段的正半圈期间可以观察到局部接触现象。 (c)2017 Elsevier Ltd.保留所有权利。

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