Inverse Load Identification in Stiffened Plate Structure Based on in situ Strain Measurement

Yihua H. Wang, Zhenhuan Zhou, Hao Xu, Shuai Li, Zhanjun Wu
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引用次数: 3

Abstract

For practical engineering structures, it is usually difficult to measure external load distribution in a direct manner, which makes inverse load identification important. Specifically, load identification is a typical inverse problem, for which the models (e.g., response matrix) are often ill-posed, resulting in degraded accuracy and impaired noise immunity of load identification. This study aims at identifying external loads in a stiffened plate structure, through comparing the effectiveness of different methods for parameter selection in regulation problems, including the Generalized Cross Validation (GCV) method, the Ordinary Cross Validation method and the truncated singular value decomposition method. With demonstrated high accuracy, the GCV method is used to identify concentrated loads in three different directions (e.g., vertical, lateral and longitudinal) exerted on a stiffened plate. The results show that the GCV method is able to effectively identify multi-source static loads, with relative errors less than 5%. Moreover, under the situation of swept frequency excitation, when the excitation frequency is near the natural frequency of the structure, the GCV method can achieve much higher accuracy compared with direct inversion. At other excitation frequencies, the average recognition error of the GCV method load identification less than 10%.
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基于原位应变测量的加筋板结构反载荷识别
对于实际工程结构,通常难以直接测量外荷载分布,这使得反荷载识别变得非常重要。具体来说,负载识别是一个典型的逆问题,其模型(如响应矩阵)往往是病态的,导致负载识别的精度下降和抗噪声能力下降。本研究旨在通过比较广义交叉验证法(GCV)、普通交叉验证法和截短奇异值分解法等不同方法在调节问题参数选择中的有效性,识别加筋板结构中的外荷载。GCV方法具有较高的精度,可用于识别施加在加筋板上的三个不同方向(例如垂直、横向和纵向)的集中载荷。结果表明,GCV方法能够有效识别多源静态载荷,相对误差小于5%。此外,在扫频激励情况下,当激励频率接近结构固有频率时,GCV方法比直接反演的精度要高得多。在其他激励频率下,GCV法载荷识别的平均识别误差小于10%。
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来源期刊
SDHM Structural Durability and Health Monitoring
SDHM Structural Durability and Health Monitoring Engineering-Building and Construction
CiteScore
2.40
自引率
0.00%
发文量
29
期刊介绍: In order to maintain a reasonable cost for large scale structures such as airframes, offshore structures, nuclear plants etc., it is generally accepted that improved methods for structural integrity and durability assessment are required. Structural Health Monitoring (SHM) had emerged as an active area of research for fatigue life and damage accumulation prognostics. This is important for design and maintains of new and ageing structures.
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