Experimental Investigations of Damage Identification for Aluminum Foam Sandwich Beams Using Two-Step Method

Xinyu He, Dongsheng Ge, Yi An
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Abstract

In the experiment, strain gauges and dynamic signal acquisition instruments are used to collect and record data, and the stochastic subspace algorithm is used to extract the first three strain modal parameters of each case. The damage amount identified by the second natural frequency based on the modified Timoshenko beam theory is more in line with the actual situation. The damage depth of case 2 and case 4 is 2 mm, and the identified damage amount is 10% and 9%, respectively. The damage depth of case 3 and case 5 is 4 mm, and the identified damage amount is 16% and 23%, respectively. The damage location information of case 6 is well identified by using the normalized strain modal shape difference index and the enhanced strain modal shape difference index. Taking the strain response signal of case 6 as an example, it is proved that the stochastic subspace strain modal parameter identification algorithm has strong anti-interference ability under the action of 1.5 times, 4 times, and 9 times noise. In addition, the method is verified by theoretical calculation and numerical simulation, and the damage law has a high degree of coincidence with the test. The experimental results show that this method expands the theoretical basis of foam metal damage degree information identification and improves the accuracy of damage location information identification and the anti-interference of parameter identification.
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使用两步法识别铝泡沫夹层梁损伤的实验研究
实验中使用应变仪和动态信号采集仪采集和记录数据,并采用随机子空间算法提取每种情况的前三个应变模态参数。基于修正的季莫申科梁理论的第二固有频率确定的破坏量更符合实际情况。案例 2 和案例 4 的破坏深度均为 2 mm,确定的破坏量分别为 10%和 9%。案例 3 和案例 5 的破坏深度为 4 毫米,确定的破坏量分别为 16% 和 23%。利用归一化应变模态形差指数和增强应变模态形差指数可以很好地识别出案例 6 的损坏位置信息。以案例 6 的应变响应信号为例,证明了随机子空间应变模态参数识别算法在 1.5 倍、4 倍和 9 倍噪声作用下具有很强的抗干扰能力。此外,该方法还通过理论计算和数值模拟进行了验证,其损伤规律与试验具有较高的吻合度。实验结果表明,该方法拓展了泡沫金属损伤程度信息识别的理论基础,提高了损伤位置信息识别的准确性和参数识别的抗干扰性。
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