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Structural health monitoring

About: Structural health monitoring is a research topic. Over the lifetime, 11727 publications have been published within this topic receiving 186231 citations.


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TL;DR: In this paper, the authors presented two novel damage indices based on empirical mode decomposition (EMD) and fast Fourier integration for identifying structural damage caused by a change in structural stiffness.
Abstract: This paper presents two novel damage indices based on empirical mode decomposition (EMD) and fast Fourier integration for identifying structural damage caused by a change in structural stiffness. The paper also demonstrates the effectiveness of the proposed damage indices formulated based on a series of coupled mathematical/engineering approaches that are used to detect damage in pipes reliably and accurately. The main approach is based on monitoring the vibration response of pipes using piezoelectric sensors and the first intrinsic mode functions (IMFs). Finite element analysis is used to simulate the response of a healthy pipe, as well as pipes with various sizes of damage. Damages are meant to represent the outcome of local corrosion (damage) with varying reduction in areas around the circumference of the pipe. The evaluated damage indices could effectively establish the location of the defects. Moreover, the evaluated energy indices could also distinguish various size defects. To demonstrate further the effectiveness of our proposed damage indices, the results are compared with other effective indices based on wavelet packet and other statistical methods reported in the literature.

58 citations

Journal ArticleDOI
TL;DR: In this paper, an energy harvesting system that converts the low frequency, non-periodic, and low acceleration vibrations present on bridges is continued and significantly extended in this work, where the mechanics of the harvester were optimized to increase its robustness and lifetime, power electronics were added, and complete system was installed on the New Carquinez suspension bridge in California.
Abstract: Advances in energy harvesting systems are needed to power wireless sensors for structural health monitoring. Research on developing a harvesting system that converts the low frequency, non-periodic, and low-acceleration vibrations present on bridges is continued and significantly extended in this work. The mechanics of the harvester were optimized to increase its robustness and lifetime, power electronics were added, and the complete system was installed on the New Carquinez suspension bridge in California. The complete results and analysis are presented in this study. The power management circuit is added to rectify and boost the low AC output of the harvester and convert it into a usable DC voltage. The harvester design is further enhanced to significantly improve performance and robustness. During short-term on-bridge testing, the system was able to charge a 10 μF capacitor to 2 V DC, and the average harvester output power ranges from 1.6 to 5.0 μW, depending on the location on the bridge, a 10× improvement over previous results. A long-term test of the harvesting system has been conducted, during which the performance of the system was monitored remotely using a wireless sensor network. The system improvements described in this study enabled continuous operation in the harsh bridge environment for 13 months starting April 30, 2012 and constitute a major milestone in the development of miniaturized motion harvesters. Finally, the system was retrieved and analyzed to understand and verify the cause of observed long-term performance changes.

58 citations

Journal ArticleDOI
TL;DR: This paper proposes and study three frameworks for Compressive Sensing in SHM systems and provides theoretical justification for each based on the equations of motion describing a simplified Multiple-Degree-Of-Freedom (MDOF) system, and supports the proposed techniques using simulations based on synthetic and real data.
Abstract: Structural Health Monitoring (SHM) systems are critical for monitoring aging infrastructure (such as buildings or bridges) in a cost-effective manner. Such systems typically involve collections of battery-operated wireless sensors that sample vibration data over time. After the data is transmitted to a central node, modal analysis can be used to detect damage in the structure. In this paper, we propose and study three frameworks for Compressive Sensing (CS) in SHM systems; these methods are intended to minimize power consumption by allowing the data to be sampled and/or transmitted more efficiently. At the central node, all of these frameworks involve a very simple technique for estimating the structure's mode shapes without requiring a traditional CS reconstruction of the vibration signals; all that is needed is to compute a simple Singular Value Decomposition. We provide theoretical justification (including measurement bounds) for each of these techniques based on the equations of motion describing a simplified Multiple-Degree-Of-Freedom (MDOF) system, and we support our proposed techniques using simulations based on synthetic and real data.

58 citations

Journal ArticleDOI
TL;DR: This paper introduces a new scheme for SHM by exploiting robust multivariate outlier statistics in order to investigate if the selected features are free from multiple outliers before such features can be selected for either supervised or unsupervised analysis.

58 citations

Journal ArticleDOI
TL;DR: A novel monitoring system for impact localisation in aluminium and composite structures, which is able to determine the impact location in real-time without a-priori knowledge of the mechanical properties of the material is proposed.
Abstract: The most commonly encountered type of damage in aircraft composite structures is caused by low-velocity impacts due to foreign objects such as hail stones, tool drops and bird strikes. Often these events can cause severe internal material damage that is difficult to detect and may lead to a significant reduction of the structure’s strength and fatigue life. For this reason there is an urgent need to develop structural health monitoring systems able to localise low-velocity impacts in both metallic and composite components as they occur. This article proposes a novel monitoring system for impact localisation in aluminium and composite structures, which is able to determine the impact location in real-time without a-priori knowledge of the mechanical properties of the material. This method relies on an optimal configuration of receiving sensors, which allows linearization of well-known nonlinear systems of equations for the estimation of the impact location. The proposed algorithm is based on the time of arrival identification of the elastic waves generated by the impact source using the Akaike Information Criterion. The proposed approach was demonstrated successfully on both isotropic and orthotropic materials by using a network of closely spaced surface-bonded piezoelectric transducers. The results obtained show the validity of the proposed algorithm, since the impact sources were detected with a high level of accuracy. The proposed impact detection system overcomes current limitations of other methods and can be retrofitted easily on existing aerospace structures allowing timely detection of an impact event.

58 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023600
20221,374
2021776
2020746
2019803
2018708