• Smart Structures and Systems
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• v.15 no.3
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• pp.699-715
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• 2015

A modal parameter based damage sensitive feature (DSF) is defined to mimic the relative change in any diagonal element of the stiffness matrix of a model of a structure. The damage assessment is performed in a statistical pattern recognition framework using empirical complementary cumulative distribution functions (ECCDFs) of the DSFs extracted from measured operational vibration response data. Methods are discussed to perform probabilistic structural health assessment with respect to the following questions: (a) "Is there a change in the current state of the structure compared to the baseline state?", (b) "Does the change indicate a localized stiffness reduction or increase?", with the latter representing a situation of retrofitting operations, and (c) "What is the severity of the change in a probabilistic sense?". To identify a range of normal structural variations due to environmental and operational conditions, lower and upper bound ECCDFs are used to define the baseline structural state. Such an approach attempts to decouple "non-damage" related variations from damage induced changes, and account for the unknown environmental/operational conditions of the current state. The damage assessment procedure is discussed using numerical simulations of ambient vibration testing of a bridge deck system, as well as shake table experimental data from a 4-story steel frame.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.4
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• pp.169-179
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• 2002

This paper presents an efficient algorithm for the estimation of damage location and severity in structure using Probabilistic Neural Network (PNN). Artificial neural network has been being used for damage assessment by many researchers, but there are still some barriers that must be overcome to improve its accuracy and efficiency. The major problems with the conventional neural network are the necessity of many training data for neural network learning and ambiguity in the relation of neural network architecture with convergence of solution. In this paper, PNN is used as a pattern classifier to overcome those problems in the conventional neural network. The basic idea of damage assessment algorithm proposed in this paper is that modal characteristics from a damaged structure are compared with the training patterns which represent the damage in specific element to determine how close it is to training patterns in terms of the probability from PNN. The training pattern that gives a maximum probability implies that the element used in producing the training pattern is considered as a damaged one. The proposed damage assessment algorithm using PNN is applied to a 2-span continuous beam model structure to verify the algorithm.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.711-730
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• 2010

This study presents the design of autonomous smart sensor nodes for damage monitoring of tendons and girders in prestressed concrete (PSC) bridges. To achieve the objective, the following approaches are implemented. Firstly, acceleration-based and impedance-based smart sensor nodes are designed for global and local structural health monitoring (SHM). Secondly, global and local SHM methods which are suitable for damage monitoring of tendons and girders in PSC bridges are selected to alarm damage occurrence, to locate damage and to estimate severity of damage. Thirdly, an autonomous SHM scheme is designed for PSC bridges by implementing the selected SHM methods. Operation logics of the SHM methods are programmed based on the concept of the decentralized sensor network. Finally, the performance of the proposed system is experimentally evaluated for a lab-scaled PSC girder model for which a set of damage scenarios are experimentally monitored by the developed smart sensor nodes.

• Smart Structures and Systems
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• v.5 no.6
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• pp.681-697
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• 2009

Limited, noisy data in vibration testing is a hindrance to the development of structural damage detection. This paper presents a method for optimizing sensor placement and performing damage detection using finite element model updating. Sensitivity analysis of the modal flexibility matrix determines the optimal sensor locations for collecting information on structural damage. The optimal sensor locations require the instrumentation of only a limited number of degrees of freedom. Using noisy modal data from only these limited sensor locations, a method based on model updating and changes in the flexibility matrix successfully determines the location and severity of the imposed damage in numerical simulations. In addition, a steel cantilever beam experiment performed in the laboratory that considered the effects of model error and noise tested the validity of the method. The results show that the proposed approach effectively and robustly detects structural damage using limited, optimal sensor information.

• Journal of Forest and Environmental Science
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• v.36 no.2
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• pp.143-155
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• 2020

A juniper pocket rot fungus, Pyrofomes demidoffii is a basidiomycetous fungus responsible for damage of living Juniperus spp. However, its effect on the residual strength and on the extent of decay of juniper's trunk was not determined in any prior studies. The purpose of this study was to study the features of J. procera infected by P. demdoffii, and to estimate the level of strength loss and decay severity in the trunk at D.B.H height using different five formulas. Infected juniper stands were examined in two Ethiopian forests through Visual Tree Assessment (VTA) followed by a slight destructive drilling of the trunk at D.B.H height. The decayed juniper tree is characterized by partially degraded lignin material at incipient stage of decay to completely degraded lignin material at final stage of decay. In the evaluated formulas, results of ANOVA showed that a significantly higher mean percentage of strength loss and decay severity were recorded in the trees of larger D.B.H categories (p<0.001). The strength loss formulas produced the same to similar patterns of sum of ranks of strength loss or decay severity in the trunk, but the differences varied significantly among D.B.H categories in Kruskal Wallis-test (p<0.001). In conclusion, the employed formulas showed similar to different degree of variability in quantification of strength loss or decay severity in the trunk. The findings of our study could be used as the baseline for further study on juniper's strength loss or decays in the trunk of Juniperus spp. and unequivocally helps to design the corresponding management as result of P. demidoffii.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.368-374
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• 2008

Multi-axial simulation table(MAST) is widely used in motor companies as the multi-axial excitor for vibration fatigue of target component, which provides the vibrational condition as close as the vehicle test. However, the vibration fatigue performance of target component can be guaranteed with MAST system only in case the input profile covers the required severity of the target component on field test. In this paper, the signal processing for multi-axial vibration fatigue test on vehicle component is presented, from the data acquisition of the target component to the derivation of input profile. To compare the severity of vibration condition between field and proving ground, the energy principle of a equivalent damage is proposed and then, it is determined the optimal combination of special events on proving ground using a sequential searching optimal algorithm. To explain the vibration methodology clearly, seat and door component of vehicle are selected as a example.

• Structural Engineering and Mechanics
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• v.36 no.5
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• pp.643-667
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• 2010

The classical flexibility difference method detects damage by observing the difference of conventional deflection flexibility matrices between pre- and post-damaged states of a structure. This method is not able to identify multiple damage scenarios, and its criteria to identify damage depend upon the boundary conditions of structures. The key point behind the inability and dependence is revealed in this study. A more feasible flexibility for damage detection, the Angle-between-String-and-Horizon (ASH) flexibility, is proposed. The physical meaning of the new flexibility is given, and synthesis of the new flexibility matrix by modal frequencies and translational mode shapes is formulated. The damage indicators are extracted from the difference of ASH flexibility matrices between the pre- and post-damaged structures. One feature of the ASH flexibility is that the components in the ASH flexibility matrix are associated with elements instead of Nodes or DOFs. Therefore, the damage indicators based on the ASH flexibility are mapped to structural elements directly, and thus they can pinpoint the damaged elements, which is appealing to damage detection for complex structures. In addition, the change in the ASH flexibility caused by damage is not affected by boundary conditions, which simplifies the criteria to identify damage. Moreover, the proposed method can determine relatively the damage severity. Because the proposed damage indicator of an element mainly reflects the deflection change within the element itself, which significantly reduces the influence of the damage in one element on the damage indicators of other damaged elements, the proposed method can identify multiple damage locations. The viability of the proposed approach has been demonstrated by numerical examples and experimental tests on a cantilever beam and a simply supported beam.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.199-209
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• 2011

In the study of traffic safety, the analysis on factors affecting crash severity and the understanding about their relationship is important to be planning and execute to improve safety of road and traffic facilities. The purpose of this study is to develop a hierarchical binomial logistic model to identify the significant factors affecting fatal injuries and vehicle damages of traffic crashes on freeway. Two models on death and total vehicle damage are developed. The hierarchical structure of response variable is composed of two level, crash-occupant and crash-vehicle. As a result, we have gotten the crash-level random effect from these hierarchical structure as well as the fixed effect of covariates, namely odds ratio. The crash on the main line and in-out section have greater damage than other facilities. Injuries and vehicle damages are severe in case of traffic violations, centerline invasion and speeding. Also, collision crash and fire occurrence is more severe damaged than other crash types. The surrounding environment of surface conditions by climate and visibility conditions by day and night is a significant factor on crash occurrence. On the orher hand, the geometric condition of road isn't.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.34 no.1
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• pp.14-22
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• 1989

Rice varieties showing different degree of resistance were compared with their yield losses due to the damage of sheath blight disease in field condition through 1985 to 1986. Gayabyeo showed the lowest value of disease severity among 5 varieties tested in 1985 and 8 in 1986. and Taebaekbyeo, Kwanakbyeo and Labelle showed higher value of disease severity under the condition of artificial or natural disease inoculation. Grain yield of Gayabyeo, a moderate resistant rice variety, was reduced by 0.3 to 5％ in the rate due to sheath blight disease damage and Taebaekbyeo. a susceptible variety. showed the highest in the rate of yield loss, 6.8 to 25.8 ％. The matured grain rate and 1000-grain weight of the matured tiller were decreased when the developing disease lesion reached to the flag leaf, and then panicle weight was decreased more than 25 ％ compared with panicle of healthy culm. In conclusion, Gayabyeo showed the lower rate of yield loss because of slow development of disease to the upper leaves after initial disease occurence on the lower parts of rice plants.

• Smart Structures and Systems
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• v.20 no.4
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• pp.427-440
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• 2017

One of the suitable structural damage detection methods using vibrational characteristics are damage-index-based methods. In this study, a damage index for identifying damages in plate structures using frequency response function (FRF) data has been provided. One of the significant challenges of identifying the damages in plate structures is high number of degrees of freedom resulting in decreased damage identifying accuracy. On the other hand, FRF data are of high volume and this dramatically decreases the computing speed and increases the memory necessary to store the data, which makes the use of this method difficult. In this study, FRF data are compressed using two-dimensional principal component analysis (2D-PCA), and then converted into damage index vectors. The damage indices, each of which represents a specific condition of intact or damaged structures are stored in a database. After computing damage index of structure with unknown damage and using algorithm of lookup tables, the structural damage including the severity and location of the damage will be identified. In this study, damage detection accuracy using the proposed damage index in square-shaped structural plates with dimensions of 3, 7 and 10 meters and with boundary conditions of four simply supported edges (4S), three clamped edges (3C), and four clamped edges (4C) under various single and multiple-element damage scenarios have been studied. Furthermore, in order to model uncertainties of measurement, insensitivity of this method to noises in the data measured by applying values of 5, 10, 15 and 20 percent of normal Gaussian noise to FRF values is discussed.