Early damage detection in structural health monitoring by a sensitivity method and DBSCAN clustering

نویسنده:
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سال
: 2016
چکیده: Early damage detection is an important and initial step in structural health monitoring (SHM)

that aims to evaluate the global state of a structure and finds whether damage is available

throughout the structure. To do this, a new sensitivity function regarding modal strain energy

(MSE) is proposed to use as a novel damage-sensitive feature. The sensitivity function is

based on proposing a new equation of modal sensitivity and using the presented equation in

the global formulation of MSE. In order to apply this sensitivity function as the damagesensitive

feature, the matrix of sensitivity of MSE is converted into a vector by the vectorization

procedure. A new density-based clustering method named DBSCAN is also presented

here to detect early damage using the vector of the sensitivity of MSE. To demonstrate the

performance and reliability of the proposed methods, the ASCE benchmark structure (Phase

I) is employed as a numerical example. Results show that the proposed sensitivity function is

sensitive to damage and can be a reliable damage-sensitive feature in the applications of

SHM. Furthermore, numerical results demonstrate that the proposed DBSCAN approach is a

robust tool for detecting damage.
کلیدواژه(گان): Early damage detection,sensitivity analysis,modal strain energy,clustering,DBSCAN
کالکشن :
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