A new damage detection method of single-layer latticed shells based on combined modal strain energy index
01 Jun 2022-Mechanical Systems and Signal Processing-Vol. 172, pp 109011-109011
TL;DR: In this article , an effective damage detection method based on the combined modal strain energy index is proposed to detect the location of the damaged members in a single-layer latticed shells.
About: This article is published in Mechanical Systems and Signal Processing.The article was published on 2022-06-01. It has received 10 citations till now. The article focuses on the topics: Modal & Vibration.
TL;DR: In this article , the use of mode-shapes, modal strain energy, wavelet transform, waveform fractal dimension and finite element model updating in damage identification is discussed and the proposed methodology for overcoming them.
TL;DR: In this article , a robust method based on Johansen cointegration was proposed for damage detection of laminated composite structures under the influence of nonstationary colored noise using condensed frequency response functions (CFRFs) as damage-sensitive features (DSF).
TL;DR: In this article , the authors focused on damage identification of laminated composite structures using vibration-based methods integrated with finite element methods, optimization techniques, signal processing methods, and machine learning algorithms.
TL;DR: In this article , the authors investigated the effects of various configurations of stiffeners in the shear walls on the damage level of the structures (5, 10, 15, and 20 floors) under earthquake excitations.
TL;DR: In this article, a new parameter called curvature mode shape is investigated as a possible candidate for identifying and locating damage in a structure, and it is shown that the absolute changes in the curvature shape are localized in the region of damage and hence can be used to detect damage.
TL;DR: A comprehensive review on modal parameter-based damage identification methods for beam- or plate-type structures is presented in this paper, and the damage identification algorithms in terms of signal processing are discussed.
Abstract: A comprehensive review on modal parameter-based damage identification methods for beam- or plate-type structures is presented, and the damage identification algorithms in terms of signal processing...
TL;DR: In this article, the authors used the analysis of vibration measurements as a tool for health monitoring of bridges, and the problem of separating abnormal changes from normal changes in the dynamic behaviour was identified.
Abstract: When using the analysis of vibration measurements as a tool for health monitoring of bridges, the problem arises of separating abnormal changes from normal changes in the dynamic behaviour Normal changes are caused by varying environmental conditions such as humidity, wind and most important, temperature The temperature may have an impact on the boundary conditions and the material properties Abnormal changes on the other hand are caused by a loss of stiffness somewhere along the bridge It is clear that the normal changes should not raise an alarm in the monitoring system (ie a false positive), whereas the abnormal changes may be critical for the structure's safety In the frame of the European SIMCES-project, the Z24-Bridge in Switzerland was monitored during almost one year before it was artificially damaged Black-box models are determined from the healthy-bridge data These models describe the variations of eigenfrequencies as a function of temperature New data are compared with the models If an eigenfrequency exceeds certain confidence intervals of the model, there is probably another cause than the temperature that drives the eigenfrequency variations, for instance damage Copyright © 2001 John Wiley & Sons, Ltd
TL;DR: Numerical results indicate that the combination of MSEBI and PSO can provide a reliable tool to accurately identify the multiple structural damage.
Abstract: A two-stage method is proposed here to properly identify the site and extent of multiple damage cases in structural systems. In the first stage, a modal strain energy based index (MSEBI) is presented to precisely locate the eventual damage of a structure. The modal strain energy is calculated using the modal analysis information extracted from a finite element modeling. In the second stage, the extent of actual damage is determined via a particle swarm optimization (PSO) using the first stage results. Two illustrative test examples are considered to assess the performance of the proposed method. Numerical results indicate that the combination of MSEBI and PSO can provide a reliable tool to accurately identify the multiple structural damage.
TL;DR: A flexible wireless smart sensor framework for full-scale, autonomous SHM that integrates the necessary software and hardware while addressing key implementation requirements is developed and validated on a full- scale a cable-stayed bridge in South Korea.
Abstract: Wireless smart sensors enable new approaches to improve structural health monitoring (SHM) practices through the use of distributed data processing. Such an approach is scalable to the large number of sensor nodes required for high-fidelity modal analysis and damage detection. While much of the technology associated with smart sensors has been available for nearly a decade, there have been limited numbers of full- scale implementations due to the lack of critical hardware and software elements. This research develops a flexible wireless smart sensor framework for full-scale, autonomous SHM that integrates the necessary software and hardware while addressing key implementation requirements. The Imote2 smart sensor platform is employed, providing the computation and communication resources that support demanding sensor network applications such as SHM of civil infrastructure. A multi-metric Imote2 sensor board with onboard signal processing specifically designed for SHM applications has been designed and validated. The framework software is based on a service-oriented architecture that is modular, reusable and extensible, thus allowing engineers to more readily realize the potential of smart sensor technology. Flexible network management software combines a sleep/wake cycle for enhanced power efficiency with threshold detection for triggering network wide operations such as synchronized sensing or decentralized modal analysis. The framework developed in this research has been validated on a full-scale a cable-stayed bridge in South Korea.