Compressive Sensing for Structural Damage Detection of Reinforced Concrete Structures

2013 ◽  
Vol 569-570 ◽  
pp. 742-750 ◽  
Author(s):  
Madhuka Jayawardhana ◽  
Xin Qun Zhu ◽  
Ranjith Liyanapathirana ◽  
Upul Gunawardana
Keyword(s):  
Energy Consumption ◽  
Reinforced Concrete ◽  
Damage Detection ◽  
Compressive Sensing ◽  
Data Storage ◽  
Structural Damage ◽  
Structural Response ◽  
High Energy ◽  
Reconstructed Signal ◽  
Detection And Localization

High energy consumption, excessive data storage and transfer requirements are prevailing issues associated with structural health monitoring (SHM) systems, especially with those employing wireless sensors. Data compression is one of the techniques being explored to mitigate the effects of these issues. Compressive sensing (CS) introduces a means of reproducing a signal with a much less number of samples than the Nyquist's rate, reducing the energy consumption, data storage and transfer cost. This paper explores the applicability of CS for SHM, in particular for damage detection and localization. CS is implemented in a simulated environment to compress SHM data. The reconstructed signal is verified for accuracy using structural response data obtained from a series of tests carried out on a reinforced concrete (RC) slab. Results show that the reconstruction was close, but not exact as a consequence of the noise associated with the responses. However, further analysis using the reconstructed signal provided successful damage detection and localization results, showing that although the reconstruction using CS is not exact, it is sufficient to provide the crucial information of the existence and location of damage.

scholarly journals Nanoscale optical writing through upconversion resonance energy transfer

2021 ◽  
Vol 7 (9) ◽  
pp. eabe2209
Author(s):  
S. Lamon ◽  
Y. Wu ◽  
Q. Zhang ◽  
X. Liu ◽  
M. Gu
Keyword(s):  
Graphene Oxide ◽  
Energy Transfer ◽  
Energy Consumption ◽  
Data Storage ◽  
High Capacity ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
High Energy ◽  
Optical Data ◽  
Upconversion Nanoparticles

Nanoscale optical writing using far-field super-resolution methods provides an unprecedented approach for high-capacity data storage. However, current nanoscale optical writing methods typically rely on photoinitiation and photoinhibition with high beam intensity, high energy consumption, and short device life span. We demonstrate a simple and broadly applicable method based on resonance energy transfer from lanthanide-doped upconversion nanoparticles to graphene oxide for nanoscale optical writing. The transfer of high-energy quanta from upconversion nanoparticles induces a localized chemical reduction in graphene oxide flakes for optical writing, with a lateral feature size of ~50 nm (1/20th of the wavelength) under an inhibition intensity of 11.25 MW cm−2. Upconversion resonance energy transfer may enable next-generation optical data storage with high capacity and low energy consumption, while offering a powerful tool for energy-efficient nanofabrication of flexible electronic devices.

scholarly journals Compressive sensing-based vibration signal reconstruction using sparsity adaptive subspace pursuit

2018 ◽  
Vol 10 (8) ◽  
pp. 168781401879087 ◽  
Author(s):  
Lin Zhou ◽  
Qianxiang Yu ◽  
Daozhi Liu ◽  
Ming Li ◽  
Shukai Chi ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Data Storage ◽  
Wireless Sensors ◽  
Signal Reconstruction ◽  
Estimation Method ◽  
Vibration Signal ◽  
Estimation Accuracy ◽  
Offshore Structure ◽  
Vibration Signals ◽  
Reconstructed Signal

Wireless sensors produce large amounts of data in long-term online monitoring following the Shannon–Nyquist theorem, leading to a heavy burden on wireless communications and data storage. To address this problem, compressive sensing which allows wireless sensors to sample at a much lower rate than the Nyquist frequency has been considered. However, the lower rate sacrifices the integrity of the signal. Therefore, reconstruction from low-dimension measurement samples is necessary. Generally, the reconstruction needs the information of signal sparsity in advance, whereas it is usually unknown in practical applications. To address this issue, a sparsity adaptive subspace pursuit compressive sensing algorithm is deployed in this article. In order to balance the computational speed and estimation accuracy, a half-fold sparsity estimation method is proposed. To verify the effectiveness of this algorithm, several simulation tests were performed. First, the feasibility of subspace pursuit algorithm is verified using random sparse signals with five different sparsities. Second, the synthesized vibration signals for four different compression rates are reconstructed. The corresponding reconstruction correlation coefficient and root mean square error are demonstrated. The high correlation and low error result mean that the proposed algorithm can be applied in the vibration signal process. Third, implementation of the proposed approach for a practical vibration signal from an offshore structure is carried out. To reduce the effect of signal noise, the wavelet de-noising technique is used. Considering the randomness of the sampling, many reconstruction tests were carried out. Finally, to validate the reliability of the reconstructed signal, the structure modal parameters are calculated by the Eigensystem realization algorithm, and the result is only slightly different between original and reconstructed signal, which means that the proposed method can successfully save the modal information of vibration signals.

Damage Assessment of a Building Subjected to a Terrorist Attack

2014 ◽  
Vol 17 (11) ◽  
pp. 1693-1704 ◽  
Author(s):  
E.L. Eskew ◽  
S. Jang
Keyword(s):  
Damage Detection ◽  
Damage Assessment ◽  
Structural Damage ◽  
Numerical Models ◽  
Terrorist Attack ◽  
Structural Response ◽  
Structural Condition ◽  
Condition Assessment ◽  
Detection Methods ◽  
Specific Element

An increasing threat of global terrorism has led to concerns about bombings of buildings, which could cause minor to severe structural damage. After such an event, it is important to rapidly assess the damage to the building to ensure safe and efficient emergency response. Current methods of visual inspection and non-destructive testing are expensive, subjective, and time consuming for emergency responders' usage immediately after an attack. On the other hand, vibration-based damage detection methods with wireless smart sensors could provide rapid assessment of structural characteristics with low cost. For blast analysis, structural response is usually determined using a simplified SDOF version of the undamaged structure, such as used in a Pressure-Impulse (P-I) Diagram, or using more complex FEM (finite element method) models. However, the simplified models cannot take into account damage caused by blast focus at a specific location or on a specific element, which may induce local failure leading to potential progressive collapse, and the more complex FEM models take too long to derive applicable results to be effective for a rapid structural assessment. In this paper, a new method to incorporate vibration-based damage detection methods to calculate the multi degree of freedom structural stiffness for determining structural condition is provided to create a framework for the rapid structural condition assessment of buildings after a terrorist attack. The stiffness parameters are generated from the modal analysis of the measured vibration on the building, which are then used in a numerical simulation to determine its structural response from the blast. The calculated structural response is then compared to limit conditions that have been developed from ASCE blast design codes to determine the damage assessment. A laboratory-scale building frame has been employed to validate the developed use of experimentally determined stiffness by comparing the P-I diagram using the experimental stiffness with that from numerical models. The reasonable match between the P-I diagrams from the numerical models and the experiments shows the positive potential of the method. The framework and examples of how to develop a rapid condition assessment are presented.

scholarly journals Structural Damage Identification Based on the Minimum System Realization and Sensitivity Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
W. R. Li ◽  
Y. F. Du ◽  
S. Y. Tang ◽  
L. J. Zhao
Keyword(s):  
Sensitivity Analysis ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Structural Information ◽  
Structural Response ◽  
Frame Structure ◽  
Structural Damage Detection ◽  
System Realization ◽  
Minimum System

On the basis of the thought that the minimum system realization plays the role as a coagulator of structural information and contains abundant information on the structure, this paper proposes a new method, which combines minimum system realization and sensitivity analysis, for structural damage detection. The structural damage detection procedure consists of three steps: (1) identifying the minimum system realization matrixes A, B, and R using the structural response data; (2) defining the mode vector, which is based on minimum system realization matrix, by introducing the concept of the measurement; (3) identifying the location and severity of the damage step by step by continuously rotating the mode vector. The proposed method was verified through a five-floor frame model. As demonstrated by numerical simulation, the proposed method based on the combination of the minimum realization system and sensitivity analysis is effective for the damage detection of frame structure. This method not only can detect the damage and quantify the damage severity, but also is not sensitive to the noise.

STUDY ON DAMAGE DETECTION OF SQUARE PYRAMID SPACE GRID STRUCTURE CONSIDERING INITIAL RANDOM DEFECTS

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Zhang Limei ◽  
Du Shoujun ◽  
Fan Meng
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Poisson Ratio ◽  
Design Method ◽  
Structural Response ◽  
Space Grid ◽  
Section Area ◽  
Different Types ◽  
Random Defects ◽  
The Ideal

Because of different types of load, material properties deviation and construction errors, structures have initial defects inevitably. Therefore structural damages emerge easily and have strong randomness. At the same time, the ideal design model often has difference with structure in service. To most structures, the initial testing dates cannot be obtained, while this initial model is very important to structural damage detection. So the ideal model needs to revise. In this paper, elastic modulus, Poisson ratio and link section area are given as initial random defects and these defects obey normal distribution which can be constructed by Monte Carlo probabilistic design method. Firstly, the sensitivity parameters to structural response will be received by PDS technology from Ansys. Next, the square pyramid space grid models with random defects were obtained. Finally, given link element damage, using the method combined curvature mode difference with wavelet transform, the link element damage can be determined. Through analysis, the effects about the initial defects to damage detection will be obtained.

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