کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4976837 | 1451843 | 2017 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Agglomerative concentric hypersphere clustering applied to structural damage detection
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The present paper proposes a novel cluster-based method, named as agglomerative concentric hypersphere (ACH), to detect structural damage in engineering structures. Continuous structural monitoring systems often require unsupervised approaches to automatically infer the health condition of a structure. However, when a structure is under linear and nonlinear effects caused by environmental and operational variability, data normalization procedures are also required to overcome these effects. The proposed approach aims, through a straightforward clustering procedure, to discover automatically the optimal number of clusters, representing the main state conditions of a structural system. Three initialization procedures are introduced to evaluate the impact of deterministic and stochastic initializations on the performance of this approach. The ACH is compared to state-of-the-art approaches, based on Gaussian mixture models and Mahalanobis squared distance, on standard data sets from a post-tensioned bridge located in Switzerland: the Z-24 Bridge. The proposed approach demonstrates more efficiency in modeling the normal condition of the structure and its corresponding main clusters. Furthermore, it reveals a better classification performance than the alternative ones in terms of false-positive and false-negative indications of damage, demonstrating a promising applicability in real-world structural health monitoring scenarios.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechanical Systems and Signal Processing - Volume 92, August 2017, Pages 196-212
Journal: Mechanical Systems and Signal Processing - Volume 92, August 2017, Pages 196-212
نویسندگان
Moisés Silva, Adam Santos, Reginaldo Santos, Eloi Figueiredo, Claudomiro Sales, João C.W.A. Costa,