期刊
4TH INTERNATIONAL CONFERENCE ON STRUCTURAL INTEGRITY (ICSI 2021)
卷 37, 期 -, 页码 292-298出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.prostr.2022.01.087
关键词
damage identification; damage indices; curvelet transform; modal analysis
资金
- European Regional Development Fund within the Activity 1.1.1.2 Post-doctoral Research Aid of the Specific Aid Objective 1.1.1 To increase the research and innovative capacity of scientific institutions of Latvia and the ability to attract external finan [1.1.1.2/VIAA/3/19/414]
This paper analyzes and compares two different approaches (damage indices and curvelet transform) for damage identification in composite plates and evaluates their sensitivity to damage, robustness to measurement and processing noise, and accuracy of damage estimation. The results clearly indicate the superiority of the curvelet transform, which not only accurately identifies damage with enhanced directional selectivity but also reduces measurement noise, making it an excellent choice for effective damage identification in various engineering structures.
Identification of a structural damage becomes critically important step of proper maintenance of structural elements being in operation according to the widely accepted damage tolerance philosophy in numerous industrial branches related to the construction engineering. Within the variety of available testing methods, vibration-based methods, due to their effectiveness and low cost, are used in such inspection. However, to detect small or early damage in structures, additional processing of the measurement results is necessary. In this paper, two principally different approaches of damage identification in composite plates based on the damage indices and the curvelet transform were analyzed and compared in the light of evaluation of sensitivity to damage, robustness to measurement and processing noise, and accuracy of estimation of a damage. The obtained results of this comparative study clearly indicate the superiority of the curvelet transform, which allowed not only properly identify damage thanks to the enhanced directional selectivity, but simultaneously reduce measurement noise, which makes it an excellent candidate for effective identification of damage in various engineering structures. (C) 2022 The Authors. Published by Elsevier B.V.
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