Damage detection in structures using a transmissibility-based Mahalanobis distance

Zhou, Yunlai; Figueiredo, Elói; Maia, N. M. M.; Sampaio, R. P. C.; Perera, Ricardo

doi:10.1002/stc.1743

Cited by 48 publications

(30 citation statements)

References 10 publications

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“…An essential stage of damage detection is outlier detection, which relies on distance measurements. Recently, specifically for SHM, various approaches have been adopted for the distance measurement during damage detection and quantification [39]. The present study uses symbolic datasets, as these are less voluminous, less specific, compact, and more …”

Section: Study Modelsmentioning

confidence: 99%

A Fiber Bragg Grating-Based Condition Monitoring and Early Damage Detection System for the Structural Safety of Underground Coal Mines Using the Internet of Things

Khan

Lee

et al. 2018

Journal of Sensors

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Accurate sensing is the key to structural health monitoring of underground coal mines while using fiber Bragg grating (FBG) sensors. However, the previously developed systems for structural monitoring of underground mines have been limited to monitoring without any capability of damage detection. Therefore, this study integrates a highly accurate FBG monitoring system and output-only data-driven approaches on an Internet of things (IoT)-based platform to develop a comprehensive mine structural safety system. This system relies on a Web 2.0 main server that runs data acquisition, data processing, and damage detection algorithms along with real-time information sharing at remote locations. This system was successfully implemented at the Hassan Kishore coal mine, situated in the Salt Range of Pakistan. Wavelength division multiplexing of the FBG strain sensors reliably captured the effects of dynamic and continuous coal excavation on the stability of mine roadway and access galleries. Principal component analysis, along with hierarchical clustering, was used to determine the damage indicator of the mine. The damage index was validated, showing the minimum value for 2% stiffness reduction. Thus, integration of FBG technology with the Internet can be effectively applied for early safety assessment of underground coal mines and information sharing in real time.

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Section: Study Modelsmentioning

confidence: 99%

A Fiber Bragg Grating-Based Condition Monitoring and Early Damage Detection System for the Structural Safety of Underground Coal Mines Using the Internet of Things

Khan

Lee

et al. 2018

Journal of Sensors

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“…The fast computational algorithm "Square Robust Distance" was used for multivariate outlier detection, as defined by Equation 8, where RD is a matrix that diagonally contains the robust Mahalanobis distance of each multivariate instance x i (i = 1, … , n), x is a matrix of n rows (instances) and p columns (variables), x is a matrix of n row with p columns with mean x j ( j = 1, … , p) from the group of instances (every row contains the same information; the column mean of all instances), and Σ −1 is the inverse covariance matrix. [60][61][62] Obtaining a chi-critical value of 11.1433 for a 97.5% quantile chi-squared distribution. [63] Detecting 136 outlier's instances FIGURE 4 General operation flow through an optical table at laboratory environment FIGURE 5 Optical scanning system measurements database from 6,020 instances, presenting the 2.56% of instances from the original OSS measurement database.…”

Section: Experimental Measurementsmentioning

confidence: 99%

Experimental image and range scanner datasets fusion in SHM for displacement detection

Rivera-Castillo

Flores-Fuentes

Rivas-López

et al. 2016

Struct. Control Health Monit.

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Summary Optical images and signals can be used to detect displacement in civil engineering structures. This paper presents a technical experimentation of a vision‐based technology and artificial intelligence algorithms methodology for structural health monitoring of new and aging structures, by a noncontact and nondestructive system. The experimental study emphasis is on the outdoor urban environment, by the detection of spatial coordinate displacement on the structures, in order to perform a damage assessment. Also, the experimental study contains both theoretical and experimental aspects of the fusion of image and range scanner datasets created using intelligent algorithms. A camera and an optical scanning system were used to generate high resolution and quality images for 2D imaging, and 3D accuracy range data from optoelectronic sensor signals. Scans at a specific area of an engineering structure were performed to measure spatial coordinates displacements, successfully verifying the effectiveness and the robustness of the proposed non‐contact and non‐destructive monitoring approach.

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“…More recently, FRFs and transmissibilities were linked to the approach based on Mahalanobis squared distance (MSD) to determine the structural condition of a monitored beam via different types of DIs [22]. Similar to a first proposal [23], the MSD algorithm presents problems, namely numerical errors to compute a large covariance matrix, when all spectral lines of the damage-sensitive features are considered.…”

Section: Introductionmentioning

confidence: 99%

Output-only structural damage detection based on transmissibility measurements and kernel principal component analysis

Santos

Silva

Santos

et al. 2019

JCIS

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Frequency response functions have been employed as damage-sensitive features in the vibration-based structural damage detection. However, the need for measuring the excitation forces arises as a remarkable limitation on the application of those features in real-world applications. As an alternative, transmissibility measurements can be explored as features with output-only nature, which implies the need for measuring only the response signals. In this paper, an output-only damage detection method is proposed, combining transmissibilities with kernel principal component analysis (KPCA). This technique is based on the pattern recognition paradigm for structural health monitoring, where feature extraction and feature classification phases are considered. In the first phase, the dimensionality of the transmissibilities is appropriately reduced by applying the KPCA algorithm. In the second phase, an outlier detection strategy is used to determine the condition of the instrumented structure. The possibility of clustering in the high-dimensional space mapped by KPCA is also reported and discussed. The proposed method is experimentally validated with transmissibilities acquired, under distinct structural conditions, from a laboratory steel beam instrumented with several accelerometers. The results demonstrate that the output-only method has high potential to be applied in a wide range of monitoring solutions, where economic issues and life-safety are primary motivations.

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Damage detection in structures using a transmissibility-based Mahalanobis distance

Cited by 48 publications

References 10 publications

A Fiber Bragg Grating-Based Condition Monitoring and Early Damage Detection System for the Structural Safety of Underground Coal Mines Using the Internet of Things

A Fiber Bragg Grating-Based Condition Monitoring and Early Damage Detection System for the Structural Safety of Underground Coal Mines Using the Internet of Things

Experimental image and range scanner datasets fusion in SHM for displacement detection

Output-only structural damage detection based on transmissibility measurements and kernel principal component analysis

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