• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• Smart Structures and Systems
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• v.17 no.6
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• pp.957-980
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• 2016

Structural damage detection (SDD) is a challenging task in the field of structural health monitoring (SHM). As an exploring attempt to the SDD problem, a hybrid self-adaptive Firefly-Nelder-Mead (SA-FNM) algorithm is proposed for the SDD problem in this study. First of all, the basic principle of firefly algorithm (FA) is introduced. The Nelder-Mead (NM) algorithm is incorporated into FA for improving the local searching ability. A new strategy for exchanging the information in the firefly group is introduced into the SA-FNM for reducing the computation cost. A random walk strategy for the best firefly and a self-adaptive control strategy of three key parameters, such as light absorption, randomization parameter and critical distance, are proposed for preferably balancing the exploitation and exploration ability of the SA-FNM. The computing performance of the SA-FNM is evaluated and compared with the basic FA by three benchmark functions. Secondly, the SDD problem is mathematically converted into a constrained optimization problem, which is then hopefully solved by the SA-FNM algorithm. A multi-step method is proposed for finding the minimum fitness with a big probability. In order to assess the accuracy and the feasibility of the proposed method, a two-storey rigid frame structure without considering the finite element model (FEM) error and a steel beam with considering the model error are taken examples for numerical simulations. Finally, a series of experimental studies on damage detection of a steel beam with four damage patterns are performed in laboratory. The illustrated results show that the proposed method can accurately identify the structural damage. Some valuable conclusions are made and related issues are discussed as well.

• Smart Structures and Systems
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• v.17 no.6
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• pp.981-994
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• 2016

Two field research stations based upon atmospheric corrosivity monitoring combined with reinforced concrete corrosion rate sensors have been established in Kuwait. This was established for the purpose of remote monitoring of building materials performance for concrete under Kuwait atmospheric environment. The two field research sites for concrete have been based upon an outcome from a research investigation intended for monitoring the atmospheric corrosivity from weathering station distributed in eight areas, and in different regions in Kuwait. Data on corrosivity measurements are essential for the development of specification of an optimized corrosion resistance system for reinforced concrete manufactured products. This study aims to optimize, characterize, and utilize long-term concrete structural health monitoring through on line corrosion measurement and to determine the feasibility and viability of the integrated anode ladder corrosion sensors embedded in concrete. The atmospheric corrosivity categories supported with GSM remote data acquisition system from eight corrosion monitoring stations at different regions in Kuwait are being classified according to standard ISO 9223. The two nominated field sites where based upon time of wetness and bimetallic corrosion rate from atmospheric data where metals and rebar's concrete are likely to be used. Eight concrete blocks with embeddable anodic ladder corrosion sensors were placed in the atmospheric zone adjacent to the sea shore at KISR site. The anodic ladder corrosion rate sensors for concrete were installed to provide an early warning system on prediction of the corrosion propagation and on developing new insights on the long-term durability performance and repair of concrete structures to lower labor cost. The results show the atmospheric corrosivity data of the environment and the feasibility of data retrieval of the corrosion potential of concrete from the embeddable sets of anodic ladder corrosion sensors.

• Smart Structures and Systems
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• v.22 no.4
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• pp.481-493
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• 2018

Ultrasonic guided waves have attracted increasing attention for non-destructive testing (NDT) and structural health monitoring (SHM) of bridge cables. They offer advantages like single measurement, wide coverage of acoustical field, and long-range propagation capability. To design defect detection systems, it is essential to understand how guided waves propagate in cables and how to select the optimal excitation frequency and mode. However, certain cable characteristics such as multiple wires, anchorage, and polyethylene (PE) sheath increase the complexity in analyzing the guided wave propagation. In this study, guided wave modes for multi-wire bridge cables are identified by using a semi-analytical finite element (SAFE) technique to obtain relevant dispersion curves. Numerical results indicated that the number of guided wave modes increases, the length of the flat region with a low frequency of L(0,1) mode becomes shorter, and the cutoff frequency for high order longitudinal wave modes becomes lower, as the number of steel wires in a cable increases. These findings were used in design of transducers for defect detection and selection of the optimal wave mode and frequency for subsequent experiments. A magnetostrictive transducer system was used to excite and detect the guided waves. The applicability of the proposed approach for detecting and locating wire breakages was demonstrated for a cable with 37 wires. The present ultrasonic guided wave method has been found to be very responsive to the number of brokenwires and is thus capable of detecting defects with varying sizes.

• Smart Structures and Systems
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• v.25 no.1
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• pp.23-35
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• 2020

It is important to take into account the thermal behavior in assessing the structural condition of bridges. An effective method of studying the temperature effect of long-span bridges is numerical simulation based on the solar radiation models. This study aims to develop a time-varying solar radiation model which can consider the real-time weather changes, such as a cloud cover. A statistical analysis of the long-term monitoring data is first performed, especially on the temperature data between the south and north anchors of the bridge, to confirm that temperature difference can be used to describe real-time weather changes. Second, a defect in the traditional solar radiation model is detected in the temperature field simulation, whereby the value of the turbidity coefficient t_u is subjective and cannot be used to describe the weather changes in real-time. Therefore, a new solar radiation model with modified turbidity coefficient γ is first established on the temperature difference between the south and north anchors. Third, the temperature data of several days are selected for model validation, with the results showing that the simulated temperature distribution is in good agreement with the measured temperature, while the calculated results by the traditional model had minor errors because the turbidity coefficient t_u is uncertainty. In addition, the vertical and transverse temperature gradient of a typical cross-section and the temperature distribution of the tower are also studied.

• Smart Structures and Systems
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• v.26 no.3
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• pp.345-360
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• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.605-611
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• 2020

The purpose of this study is to analyze the perception and demand of industrial sites necessary for the development of ICT-based products for young child, to seek effective support plans for ICT-based young child product developers that help with smart child rearing in the era of low birthrate. To this end, first, it was found that various and active promotions of specialized organizations or centers that have jointly utilized equipment are necessary. Second, it was found that many companies were willing to use equipment for the development of ICT-based young child's products. Third, the demand for corporate support was to provide information, equipment utilization, technical guidance and biometric information. Based on these results, it was proposed to expand related infrastructure that can efficiently support the development of ICT-based products for young child.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.135-141
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• 2017

Recently, as elderly people suffering from chronic diseases have increased and disasters such as traffic accidents have increased, urgent rescue workers and doctors need to respond effectively to such emergencies. For elderly people, the difficulty in communicating their condition especially the health condition during disaster is one of the problems in which delay on immediate handling by rescue team can cause death. Providing a solution for this problem is one of the main issues in our research. In this paper, we use the QR code to communicate the minimum personal information and medical history needed for emergency medical treatment to emergency medical personnel, and to transmit the medical history and treatment data to the doctors of the hospital through QR code and fingerprint recognition, respectively. Especially, by using both QR code of smart phone and fingerprint of individual, we can protects personal information and strengthens privacy and security of medical information by allowing only authorized physicians to check medical records of the old patient.

• Physical Therapy Rehabilitation Science
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• v.9 no.1
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• pp.43-48
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• 2020

Objective: Breast cancer-related lymphedema (BCRL) is a major sequela after surgery or radiotherarpy for breast cancer. Manual lymphatic drainage (MLD) is designed to reduce lymph swelling by facilitating lymphatic drainage. This study attempted to determine the histologic changes in the skin and subcutaneous layer, and the immediate effect of MLD in decreasing lymphedema using ultrasound imaging, which is the method used most commonly to eliminate BCRL. Design: A single-group experimental study. Methods: Five subjects who were diagnosed with hemiparetic upper extremity lymphedema more than six months after breast cancer surgery participated in the study. MLD was performed for 60 minutes in the order of the thorax, breast, axilla, and upper arm of the affected side. In order to determine the effect of MLD, ultrasound imaging and limb volume were assessed. Two measurement tools were used for asessing lymphedema thickness among the pretest, posttest, and 30-minute follow-up period. Results: Significant diferences in ultrasound imaging and upper limb volume were found between the affected side and non-affected side (p<0.05). On the affected side, although ultrasound imaging showed a significant decrease after MLD (p<0.05), there were no significant difference in upper limb volume when compared to the baseline. Conclusions: In this study, a significant decrease in lymphedema by MLD was demonstrated by ultrasound imaging, which is considered to be more useful in assessing histological changes than limb volume measurements. Further research on the protocol for eliminating lymphedema will be needed.

• Physical Therapy Rehabilitation Science
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• v.9 no.2
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• pp.105-112
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• 2020

Objective: To investigate the effects of training using a trunk control robot (TCR) system combined with conventional therapy (CT) on balance and gait abilities in persons with chronic stroke. Design: Two-group pretest-posttest design. Methods: Thirty-five subjects with chronic stroke were randomly assigned to either the TCR group (n=17) or the trunk extension-training (TET) group (n=18). Both groups performed CT for 30 minutes, after which the TCR group performed TCR training and the TET group performed trunk extension training for 20 minutes. Both groups performed the therapeutic interventions 3 days per week for 6 weeks. Balance ability was evaluated using the Berg Balance Scale (BBS), and the Timed Up-and-Go (TUG) test. Gait ability was measured using the 10 m Walk Test (10MWT) and the NeuroCom Smart Balance Master. Results: TCR group showed significant improvements in static balance (weight bearing) and dynamic balance (weight shifting speed, weight shifting direction, BBS, and TUG), 10MWT, gait speed, and step width (p<0.05); step length was not significant. The TET group showed a significant partial improvement of dynamic balance (weight shifting speed, weight shifting direction, BBS, and 10MWT (p<0.05), but the improvements in static balance, TUG, gait speed, and step width and step length was not significant. Additionally, significant differences in static balance, dynamic balance (weight shifting speed, weight shifting direction, BBS, and TUG), 10MWT, gait speed, and step width were detected between groups (p<0.05). Conclusions: TCR training combined with CT is effective in improving static and dynamic balance, as well as gait abilities in persons with chronic stroke.