• Smart Structures and Systems
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• 제21권4호
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• pp.449-467
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• 2018

In this paper, a theoretical and numerical study on bridge simultaneous damage detection procedure for identifying both the system parameters and input excitation mass, are presented. This method is called 'Adjoint Variable Method' which is an iterative gradient-based model updating method based on the dynamic response sensitivity. The main advantage of proposed method is inclusion of an analytical method to augment the accuracy and speed of the solution. Moving mass is a model which takes into account the inertia effects of the vehicle. This interaction model is a time varying system and proposed method is capable of detecting damage in this variable system. Robustness of proposed method is illustrated by correctly detection of the location and extension of predetermined single, multiple and random damages in all ranges of speed and mass ratio of moving vehicle. A comparison study of common sensitivity and proposed method confirms its efficiency and performance improvement in sensitivity-based damage detection methods. Various sources of errors including the effects of measurement noise and initial assumption error in stability of method are also discussed.

• Smart Structures and Systems
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• 제16권6호
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• pp.1107-1132
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• 2015

A damage detection algorithm based on neuro fuzzy hybrid system is presented in this study for location and severity predictions of cracks in beam-like structures. A combination of eigenfrequencies and rotation deviation curves are utilized as input to the soft computing technique. Both single and multiple damage cases are considered. Theoretical expressions leading to modal properties of damaged beam elements are provided. The beam formulation is based on Euler-Bernoulli theory. The cracked section of beam is simulated employing discrete spring model whose compliance is computed from stress intensity factors of fracture mechanics. A hybrid neuro fuzzy technique is utilized to solve the inverse problem of crack identification. Two different neuro fuzzy systems including grid partitioning (GP) and subtractive clustering (SC) are investigated for the highlighted problem. Several error metrics are utilized for evaluating the accuracy of the hybrid algorithms. The study is the first in terms of 1) using the two models of neuro fuzzy systems in crack detection and 2) considering multiple damages in beam elements employing the fused neuro fuzzy procedures. At the end of the study, the developed hybrid models are tested by utilizing the noise-contaminated data. Considering the robustness of the models, they can be employed as damage identification algorithms in health monitoring of beam-like structures.

• Structural Monitoring and Maintenance
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• 제7권2호
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• pp.125-147
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• 2020

Damage detection of structures is one of the most important topics in structural health monitoring. In practice, the response is not available at all structural degrees of freedom, and due to the installation of sensors at some degrees of freedom, responses exist only in limited number of degrees of freedom. This paper is investigated the damage detection of structures by applying two approaches, AllDOF and Dynamic Condensation Method (DCM), based on the Modified Modal Strain Energy Method (MMSEBI). In the AllDOF method, mode shapes in all degrees of freedom is available, but in the DCM the mode shapes only in some degrees of freedom are available. Therefore by methods like the DCM, mode shapes are obtained in slave degrees of freedom. So, in the first step, the responses at slave degrees of freedom extracted using the responses at master degrees of freedom. Then, using the reconstructed mode shape and obtaining the modified modal strain energy, the damages are detected. Two standard examples are used in different damage cases to evaluate the accuracy of the mentioned method. The results showed the capability of the DCM is acceptable for low mode shapes to detect the damage in structures. By increasing the number of modes, the AllDOF method identifies the locations of the damage more accurately.

• 디지털산업정보학회논문지
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• 제13권1호
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• pp.69-78
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• 2017

As the smartphone-based devices are diffused and developed rapidly, they provide the convenience to the users. The abovementioned sentence technologies are being used not only in the existing sensor and wireless network technology but also in the application services of the diverse fields application services such as smart appliance, smart car, smart health care, etc. and the new fusion paradigm from the industry is presented by undertaking the researches in diverse area by the enterprises and research institutions. However, the smart environment exposes its weaknesses in the mobile terminal area, existing wireless network and IT security area. In addition, due to new and variant ways of attack, not only the critical information are disclosed However also the financial damages occur. This paper proposed the protocol to perform the smartphone-based safe device monitoring and safe communication. The proposed protocol designed the management procedure of registration, identification, communication protocol and device update management protocol and the safety against the attack techniques such as the an-in-the-middle-attack, impersonation attack, credential threat, information leaks and privacy invasion was analyzed. It was observed that the proposed protocol showed the performance improved by approximately 52% in the communication process than the existing system.

• Smart Structures and Systems
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• 제3권1호
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• pp.23-49
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• 2007

Wavelet transforms are the emerging signal-processing tools for damage identification and time-frequency localization. A small perturbation in a static or dynamic displacement profile could be captured using multi-resolution technique of wavelet analysis. The paper presents the wavelet analysis of damaged linear structural elements using DB4 or BIOR6.8 family of wavelets. Starting with a localized reduction of EI at the mid-span of a simply supported beam, damage modeling is done for a typical steel and reinforced concrete beam element. Rotation and curvature mode shapes are found to be the improved indicators of damage and when these are coupled with wavelet analysis, a clear picture of damage singularity emerges. In the steel beam, the damage is modeled as a rotational spring and for an RC section, moment curvature relationship is used to compute the effective EI. Wavelet analysis is performed for these damage models for displacement, rotation and curvature mode shapes as well as static deformation profiles. It is shown that all the damage indicators like displacement, slope and curvature are magnified under higher modes. A localization scheme with arbitrary location of curvature nodes within a pseudo span is developed for steady state dynamic loads, such that curvature response and damages are maximized and the scheme is numerically tested and proved.

• The Plant Pathology Journal
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• 제32권1호
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• pp.65-69
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• 2016

In plant virus ecology, weeds are regarded as wild reservoirs of viruses and as potential sources for insect-mediated transmission of viruses. During field surveys in 2013-2014, three Leonurus sibiricus plants showing virus-like symptoms were collected from pepper fields in Daegu, Seosan, and Danyang in Korea. Molecular diagnosis assays showed that the collected L. sibiricus samples were infected with either Tomato spotted wilt virus (TSWV), Pepper mild mottle virus (PMMoV), or Beet western yellow virus (BWYV), respectively. Since this is the first identification of TSWV, PMMoV, and BWYV from L. sibiricus, complete genome sequences of three virus isolates were determined to examine their phylogenetic relationships with the previously reported strains and isolates. Phylogenetic analyses performed using full genome sequences of the viruses showed the isolates of TSWV and PMMoV obtained from L. sibiricus are closely related to the pepper isolates of the corresponding viruses. Our results suggest that L. sibiricus could act an alternative host and reservoir of viruses that cause damages in pepper fields.

• Fisheries and Aquatic Sciences
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• 제22권7호
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• pp.14.1-14.8
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• 2019

Olive flounder (Paralichthys olivaceus) is the major species developed for aquaculture in South Korea. Over the long history of olive flounder aquaculture, complex and diverse diseases have been a major problem, negatively impacting industrial production. Vibriosis is a prolific disease which continuously damages olive flounder aquaculture. A bacterial disease survey was performed from January to June 2017 on 20 olive flounder farms on Jeju Island. A total of 1710 fish were sampled, and bacteria from the external and internal organs of 560 fish were collected. Bacterial strains were identified using 16 s rRNA sequencing. Twenty-seven species and 184 strains of Vibrio were isolated during this survey, and phylogenetic analysis was performed. Bacterial isolates were investigated for the distribution of pathogenic and non-pathogenic species, as well as bacterial presence in tested organs was characterized. V. gigantis and V. scophthalmi were the dominant non-pathogenic and pathogenic strains isolated during this survey, respectively. This study provides data on specific Vibrio spp. isolated from cultured olive flounder in an effort to provide direction for future research and inform aquaculture management practices.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.13-13
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• 2011

The Rio Grande Compact Commission, in collaboration with local water management entities, water users and universities established a three state Rio Grande The Rio Grande Compact Commission, in collaboration with local water management entities, water users and universities established a three state Rio Grande Salinity Management Program. The objectives of the Rio Grande Project Salinity Management Program are to reduce salinity concentrations, loading, and salinity impacts in the Rio Grande basin for the 270 mile river reach from San Acacia, New Mexico to Fort Quitman, Texasto increase usable water supplies for agricultural, urban, and environmental purposes. The focus of this first phase of the program is the development of baseline salinity and hydrologic information and a preliminary assessment of the economic impacts of salinity. An assessment of the economic impacts of salinity in this region was conducted by scientists at Texas A&M University's AgriLife Research Center at El Paso and New Mexico State University. Economic damages attributable to high salinity of Rio Grandewater were estimated for residential, agricultural, municipal, and industrial uses. The major impact issues addressed were: who is being affected the types of economic impacts the magnitude of economic damages overall and by user category and identification of threshold-effect levels for different types of water use. Salinity concentrations in this 270 mile reach of the river typically range from 480 ppm to 1,200 ppm, but can exceed 3,000 ppm in the lower section of this reach. Economic impacts include reductions in agricultural yields, reduced water appliance life, equipment replacement costs, and increased water supply costs. This preliminary economic assessment indicates annual damages of $10.5 million from increased water salinity. Under current water uses, municipal and industrial uses account for 75% of the total estimated impacts. However, agricultural impacts are based on current crop pattern yield reductions and, salinity leaching requirements and do not account for the impacts of reduced revenue from having to grow salinity tolerant, lower value crops. Actual damages are anticipated to be significantly higher with the inclusion of these additional agricultural impacts plus the future impacts from the growing population in the region. A more comprehensive economic analysis is planned for the second phase of this program. Results of the economic analysis are being used to determine the feasiblity of salinity control alternatives and what salinity reduction control measures will be pursued.

• Smart Structures and Systems
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• 제15권4호
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• pp.1121-1137
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• 2015

This study presents probabilistic-based damage identification technique for highlighting damage in metallic structures. This technique utilizes distributed piezoelectric transducers to generate and monitor the ultrasonic Lamb wave with narrowband frequency. Diagnostic signals were used to define the scatter signals of different paths. The energy of scatter signals till different times were calculated by taking root mean square of the scatter signals. For each pair of parallel paths an error function based on the energy of scatter signals is introduced. The resultant error function then is used to estimate the probability of the presence of damage in the monitoring area. The presented method with an autofocusing feature is applied to aluminum plates for method verification. The results identified using both simulation and experimental Lamb wave signals at different central frequencies agreed well with the actual situations, demonstrating the potential of the presented algorithm for identification of damage in metallic structures. An obvious merit of the presented technique is that in addition to damages located inside the region between transducers; those who are outside this region can also be monitored without any interpretation of signals. This novelty qualifies this method for online structural health monitoring.

• Smart Structures and Systems
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• 제11권6호
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• pp.589-604
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• 2013

Identification of damage has become an evolving area of research over the last few decades with increasing the need of online health monitoring of the large structures. The visual damage detection can be impractical, expensive and ineffective in case of large structures, e.g., offshore platforms, offshore pipelines, multi-storied buildings and bridges. Damage in a system causes a change in the dynamic properties of the system. The structural damage is typically a local phenomenon, which tends to be captured by higher frequency signals. Most of vibration-based damage detection methods require modal properties that are obtained from measured signals through the system identification techniques. However, the modal properties such as natural frequencies and mode shapes are not such good sensitive indication of structural damage. Identification of damaged jacket type offshore platform members, based on wavelet packet transform is presented in this paper. The jacket platform is excited by simple wave load. Response of actual jacket needs to be measured. Dynamic signals are measured by finite element analysis result. It is assumed that this is actual response of the platform measured in the field. The dynamic signals first decomposed into wavelet packet components. Then eliminating some of the component signals (eliminate approximation component of wavelet packet decomposition), component energies of remained signal (detail components) are calculated and used for damage assessment. This method is called Detail Signal Energy Rate Index (DSERI). The results show that reduced wavelet packet component energies are good candidate indices which are sensitive to structural damage. These component energies can be used for damage assessment including identifying damage occurrence and are applicable for finding damages' location.