• Steel and Composite Structures
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• v.49 no.4
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• pp.407-417
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• 2023

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• Structural Engineering and Mechanics
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• v.71 no.1
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• pp.57-63
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• 2019

During the last two decades, much joint research regarding vibration based methods has been done, leading to developing various algorithms and techniques. These algorithms and techniques can be divided into modal methods and signal methods. Although modal methods have been widely used for health monitoring and damage detection, signal methods due to higher efficiency have received considerable attention in various fields, including aerospace, mechanical and civil engineering. Signal-based methods are derived directly from the recorded responses through signal processing algorithms to detect damage. According to different signal processing techniques, signal-based methods can be divided into three categories including time domain methods, frequency domain methods, and time-frequency domain methods. The frequency domain methods are well-known and interest in using them has increased in recent years. To determine dynamic behaviours, to identify systems and to detect damages of bridges, different methods and algorithms have been proposed by researchers. In this study, a new algorithm to detect seismic damage in the bridge's piers is suggested. To evaluate the algorithm, an analytical model of a bridge with simple spans is used. Based on the algorithm, before and after damage, the bridge is excited by a sine force, and the piers' responses are measured. The dynamic specifications of the bridge are extracted by Power Spectral Density function. In addition, the Least Square Method is used to detect damage in the bridge's piers. The results indicate that the proposed algorithm can identify the seismic damage effectively. The algorithm is output-only method and measuring the excitation force is not needed. Moreover, the proposed approach does not need numerical models.

• Smart Structures and Systems
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• v.17 no.3
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• pp.363-389
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• 2016

Deficient modes that cannot be always identified from different sets of measurement data may exist in the application of operational modal analysis such as the stochastic subspace identification techniques in large-scale civil structures. Based on a recent work using the long-term ambient vibration measurements from an instrumented cable-stayed bridge under different wind excitation conditions, a benchmark problem is launched by taking the same bridge as a test bed to further intensify the exploration of mode identifiability. For systematically assessing this benchmark problem, a recently developed SSI algorithm based on an alternative stabilization diagram and a hierarchical sifting process is extended and applied in this research to investigate several sets of known and blind monitoring data. The evaluation of delicately selected cases clearly distinguishes the effect of traffic excitation on the identifiability of the targeted deficient mode from the effect of wind excitation. An additional upper limit for the vertical acceleration amplitude at deck, mainly induced by the passing traffic, is subsequently suggested to supplement the previously determined lower limit for the wind speed. Careful inspection on the shape vector of the deficient mode under different excitation conditions leads to the postulation that this mode is actually induced by the motion of the central tower. The analysis incorporating the tower measurements solidly verifies this postulation by yielding the prevailing components at the tower locations in the extended mode shape vector. Moreover, it is also confirmed that this mode can be stably identified under all the circumstances with the addition of tower measurements. An important lesson learned from this discovery is that the problem of mode identifiability usually comes from the lack of proper measurements at the right locations.

• Smart Structures and Systems
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• v.11 no.6
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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.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.363-379
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• 2013

Dynamic displacement of structures is an important index for in-service structural condition and behavior assessment, but accurate measurement of structural displacement for large-scale civil structures such as long-span bridges still remains as a challenging task. In this paper, a vision-based dynamic displacement measurement system with the use of digital image processing technology is developed, which is featured by its distinctive characteristics in non-contact, long-distance, and high-precision structural displacement measurement. The hardware of this system is mainly composed of a high-resolution industrial CCD (charge-coupled-device) digital camera and an extended-range zoom lens. Through continuously tracing and identifying a target on the structure, the structural displacement is derived through cross-correlation analysis between the predefined pattern and the captured digital images with the aid of a pattern matching algorithm. To validate the developed system, MTS tests of sinusoidal motions under different vibration frequencies and amplitudes and shaking table tests with different excitations (the El-Centro earthquake wave and a sinusoidal motion) are carried out. Additionally, in-situ verification experiments are performed to measure the mid-span vertical displacement of the suspension Tsing Ma Bridge in the operational condition and the cable-stayed Stonecutters Bridge during loading tests. The obtained results show that the developed system exhibits an excellent capability in real-time measurement of structural displacement and can serve as a good complement to the traditional sensors.

• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.459-466
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• 2011

Sleep diseases such as snoring and sleep apnea are physically, mentally harmful and results serious health problems. Snoring, known as breathing noise, is caused by coupled oscillation of the airway when the air passes through the trachea, and sleep apnea is caused by upper airway blockage. In order to solve these problems, many attempts have been made to detect the snoring during sleep and alleviate it. In this study, a new sensing system and analysis algorithm were developed in order to detect snoring sounds correctly under various sleep environments. Two polyvinylidene fluoride (PVDF) vibration sensors were used inside the pillow. The first PVDF sensor detects vibration transmitted through skull caused by snoring. And the second PVDF sensor detects both snoring sounds and ambient noises. The signals of two sensors were acquired through the designed analog circuits, and analyzed for snoring detection. Ten volunteers were participated for the experiment under five different conditions. Data from two PVDF sensors were processed by the established analysis algorithm, and snoring sounds were compared to noises. The results indicated that the energy of snoring is 70% bigger than that of ambient noise, which proves effectiveness of sensing system and analysis algorithm. Further study would be continued for more wide clinical studies with various environment noises. Based on this study, development of anti-snore pillow and sleep monitoring system for comfort sleep could be developed.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.3068-3084
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• 2021

Investigations of large commercial aircraft impact effect on nuclear power plant (NPP) buildings have been drawing extensive attentions, particularly after the 9/11 event, and this paper aims to experimentally assess the damage and vibrations of NPP buildings subjected to aircraft crash. In present Part I, two shots of reduce-scaled model test of aircraft impacting on NPP building were carried out. Firstly, the 1:15 aircraft model (weighs 135 kg) and RC NPP model (weighs about 70 t) are designed and prepared. Then, based on the large rocket sled loading test platform, the aircraft models were accelerated to impact perpendicularly on the two sides of NPP model, i.e., containment and auxiliary buildings, with a velocity of about 170 m/s. The strain-time histories of rebars within the impact area and acceleration-time histories of each floor of NPP model are derived from the pre-arranged twenty-one strain gauges and twenty tri-axial accelerometers, and the whole impact processes were recorded by three high-speed cameras. The local penetration and perforation failure modes occurred respectively in the collision scenarios of containment and auxiliary buildings, and some suggestions for the NPP design are given. The maximum acceleration in the 1:15 scaled tests is 1785.73 g, and thus the corresponding maximum resultant acceleration in a prototype impact might be about 119 g, which poses a potential threat to the nuclear equipment. Furthermore, it was found that the nonlinear decrease of vibrations along the height was well reflected by the variations of both the maximum resultant vibrations and Cumulative Absolute Velocity (CAV). The present experimental work on the damage and dynamic responses of NPP structure under aircraft impact is firstly presented, which could provide a benchmark basis for further safety assessments of prototype NPP structure as well as inner systems and components against aircraft crash.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.5
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• pp.1-11
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• 2008

Wireless Sensor Networks is applied to improvement of life convenience or service like U-City as well as environment pollution, tunnel and structural health monitoring, storm, and earthquake diagnostic system. To increase the usability of sensor data and applicability, mobile devices and their facilities allow the applications of sensor networks to give mobile users and actuators the results of event detection at anytime and anywhere. In this paper, we present MUSNEMO(Multi-sensor centric Ubiquitous Smart sensor NEtwork using Mobile devices) developed system for providing more efficient and valuable information services with a variety of mobile devices and network camera integrated to WSN. Our system is performed based on IEEE 802.15.4 protocol stack. To validate system usability, we built sensor network environments where were equipped with five application sensors such magnetic, photodiode, microphone, motion and vibration. We also built and tested proposed MUSNEMO to provide a novel model for event detection systems with mobile framework.

• Smart Structures and Systems
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• v.16 no.1
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• pp.223-242
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• 2015

Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases.

• Smart Structures and Systems
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• v.13 no.2
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• pp.219-233
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• 2014

In a companion paper, Pasala and Nagarajaiah analytically and experimentally validate the Adaptive Length Pendulum Smart Tuned Mass Damper (ALP-STMD) on a primary structure (2 story steel structure) whose frequencies are time invariant (Pasala and Nagarajaiah 2012). In this paper, the ALP-STMD effectiveness on a primary structure whose frequencies are time varying is studied experimentally. This study experimentally validates the ability of an ALP-STMD to adequately control a structural system in the presence of real time changes in primary stiffness that are detected by a real time observer based system identification. The experiments implement the newly developed Adaptive Length Pendulum Smart Tuned Mass Damper (ALP-STMD) which was first introduced and developed by Nagarajaiah (2009), Nagarajaiah and Pasala (2010) and Nagarajaiah et al. (2010). The ALP-STMD employs a mass pendulum of variable length which can be tuned in real time to the parameters of the system using sensor feedback. The tuning action is made possible by applying a current to a shape memory alloy wire changing the effective length that supports the damper mass assembly in real time. Once a stiffness change in the structural system is detected by an open loop observer, the ALP-STMD is re-tuned to the modified system parameters which successfully reduce the response of the primary system. Significant performance improvement is illustrated for the stiffness modified system, which undergoes the re-tuning adaptation, when compared to the stiffness modified system without adaptive re-tuning.