• Smart Structures and Systems
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• v.15 no.3
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• pp.717-733
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• 2015

Modal parameters of a structure are commonly used quantities for system identification and damage detection. With a limited number of studies on the statistics assessment of modal parameters, this paper presents procedures to properly account for the uncertainties present in the process of extracting modal parameters. Particularly, this paper focuses on how to deal with the measurement error in an ambient vibration test and the modeling error resulting from a modal parameter extraction process. A bootstrap approach is adopted, when an ensemble of a limited number of noised time-history response recordings is available. To estimate the modeling error associated with the extraction process, a model prediction expansion approach is adopted where the modeling error is considered as an "adjustment" to the prediction obtained from the extraction process. The proposed procedures can be further incorporated into the probabilistic analysis of applications where the modal parameters are used. This study considers the effects of the measurement and modeling errors and can provide guidance in allocating resources to improve the estimation accuracy of the modal data. As an illustration, the proposed procedures are applied to extract the modal data of a damaged beam, and the extracted modal data are used to detect potential damage locations using a damage detection method. It is shown that the variability in the modal parameters can be considered to be quite low due to the measurement and modeling errors; however, this low variability has a significant impact on the damage detection results for the studied beam.

• Steel and Composite Structures
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• v.28 no.2
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• pp.223-231
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• 2018

Nowadays, there are a great number of various structures that have been retrofitted by using different FRP Composites. Due to this, more researches need to be conducted to know more the characteristics of these structures, not only that but also a comparison among them before and after the retrofitting is needed. In this research, a model steel structure is tested using a bench-scale earthquake simulator on the shake table, using recorded micro tremor data, in order to get the dynamic behaviors. Columns of the model steel structure are then retrofitted by using GFRP composite, and then tested on the Quanser shake table by using the recorded micro tremor data. At this stage, it is needed to evaluate the dynamic behaviors of the retrofitted model steel structure. Various types of methods of OMA, such as EFDD, SSI, etc. are used to take action in the ambient responses. Having a purpose to learn more about the effects of GFRP composite, experimental model analysis of both types (retrofitted and no-retrofitted models) is conducted to evaluate their dynamic behaviors. There is a provision of ambient excitation to the shake table by using recorded micro tremor ambient vibration data on ground level. Furthermore, the Enhanced Frequency Domain Decomposition is used through output-only modal identification. At the end of this study, moderate correlation is obtained between mode shapes, periods and damping ratios. The aim of this research is to show and determine the effects of GFRP Composite implementation on structural responses of the model steel structure, in terms of changing its dynamical behaviors. The frequencies for model steel structure and the retrofitted model steel structure are shown to be 33.916% in average difference. Finally, it is shown that, in order to evaluate the period and rigidity of retrofitted structures, OMA might be used.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.4
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• pp.121-128
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• 2003

In recent years, various artificial neural network algorithms are used in the damage assessment of civil infrastructures. So far, many researchers have used the artificial neural network as a pattern classifier for the structural damage assessment but, in this paper, the neural network is used as a structural reanalysis tool not as a pattern classifier. For the model updating using the optimization algorithm, the summation of the absolute differences in the structural vibration modes between undamaged structures and damaged ones is considered as an objective function. The stiffness of structural components are treated as unknown parameters to be determined. The structural damage detection is achieved using model updating based on the optimization techniques which determine the estimated stiffness of components minimizing the objective function. For the verification of the proposed damage identification algorithm, it is numerically applied to a simply supported bridge model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1207-1213
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• 2007

This paper has researched water supply facilities management using real-time water utility monitoring system based on USN(Ubiquitous Sensor Network) which is consisted of wireless sensors transferring waterworks facilities md treatment information about a valve-room and flowmeter-room of water supply installation. In the manholes, it was installed with flowmeter, pressure sensors, vibration sensors, Co-sensors, and hydro-thermograph sensors. These measurement values which are received by PDA are used for facilities operation on the spot safely and conveniently. It has also provided safe installation management via CDMA(Code Division Multiple Access) network which transfers data to remote servers to monitoring at a distance place. With safety management system of water supply facilities on USN technology convenience and safety is increased in real situation, and it is expected that we can supply clean water to people as much safer and more effective water supply installation management.

• 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.

• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.147-152
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• 2023

Mostly in motor fault detection the instantaneous values 3 axis vibration and 3phase current in time domain are acquired and converted to frequency domain. Vibrations are more useful in diagnosing the mechanical faults and motor current has remained more useful in electrical fault diagnosis. With having some experience and knowledge on the behavior of acquired data the electrical and mechanical faults are diagnosed through signal processing techniques or combine machine learning and signal processing techniques. In this paper, a single-layer LSTM based condition monitoring system is proposed in which the instantaneous values of three phased motor current are firstly acquired in simulated motor in in health and supply imbalance conditions in each of three stator currents. The acquired three phase current in time domain is then used to train a LSTM network, which can identify the type of fault in electrical supply of motor and phase in which the fault has occurred. Experimental results shows that the proposed single layer LSTM algorithm can identify the electrical supply faults and phase of fault with an average accuracy of 88% based on the three phase stator current as raw data without any processing or feature extraction.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.82-89
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• 2023

Due to the characteristics of ship structure, the compartment structure is complicated and narrow, so safety accidents frequently occur during the work process. The main causes of accidents include structural collisions, falling objects, toxic substance leaks, fires, explosions, asphyxiation, and more. Understanding the on-site conditions of workers during accidents is crucial for mitigating damages. In order to ensure safety, the on-site situation is monitored using CCTV in the ship, but it is difficult to prevent accidents with the existing method. To address this issue, a smart safety helmet equipped with location identification and voice/video communication capabilities is being developed as a safety technology. Additionally, the smart safety helmet incorporates environmental sensors for temperature, humidity, vibration, noise, tilt (gyro sensor), and gas detection within the work area. These sensors can notify workers wearing the smart safety helmet of hazardous situations. By utilizing the smart safety helmet and environmental sensors, the safety of workers aboard ships can be enhanced.

• Journal of the Microelectronics and Packaging Society
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• v.13 no.3 s.40
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• pp.9-12
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• 2006

We have designed and fabricated micro power generators by electroplating which is important in MEMS(micro electro mechanical system) technique. We have electroplated MEMS coils on the glass substrates and have chosen one of these coils for experiments. The thickness, width, and length of the coil are $7{\mu}m,\;20{\mu}m$, and 1.6 m, respectively. We have analyzed the structure of MEMS coil by SEM. We have made a vibrating system for reproducible results in measurement. With reciprocating a magnet on the surface of a fabricated winding coil, the micro power generator produce an alternating voltage. We have changed the vibrational frequency from 0.5 Hz to 8 Hz. The generated voltage was 106 mV at 3 Hz and 198 mV at 6 Hz. We aim at the micro power generator which can change vibration energy to useful electric energy.

• Economic and Environmental Geology
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• v.33 no.5
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• pp.391-404
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• 2000

This study investigated the geochemical characteristics of mine drainage discharged from an abandoned coal mine in the Hwasoon area. Surface water samples were collected from 23 locations along the Hancheon creek. The concentration of Zn and Cu in stream waters was highest at low pH (3.53), whereas the content of TDS and TDI was highest at high pH (7.78) due to the concentration of Ca, $HCO_3$ and $SO_4$. At the upstream site, the Ba, Fe, Mn, Zn, and $SO_4$ contents were relatively high but decreased significantly with the distance from the coal mine. On the contrary, the Na and $NO_3$ contents were low at the upstream site but increased downstream. Yellow precipitate material collected in the Hancheon consisted mainly of iron and LOI. This yellow precipitate was heated from 100 to $900^{\circ}C$ for 1 hour. With increasing temperature, the intensity of hematite peaks were sharply produced in X-ray pattern and the absorption band Fe-O of hematite increased in IR due to dehydration and melting. The yellow to brown precipitate and evaporite materials were collected by a air-dry from the acid mine water at the laboratory. After drying, the concentration of ions in the acid water samples increased progressively in oversaturation with respect to either gypsum, ferrohexahydrite or quenstedetite. The X-ray powder diffraction studies identified that the precipitated and evaporated materials after drying were well crystallized gypsum, ferrohexahydrite and quenstedetite. Diagnostic peaks used for identification of gypsum were the 7.65, 4.28, 3.03, 2.87 and 2.48$\AA$ peaks and those for ferrohexahydrite were the 5.46, 5.12, 4.89, 4.44, 4.05, 3.62, 3.46, 3.40, 3.20, 3.03, 2.94, 2.53, 2.28, 2.07, 1.88 and 1.86${\AA} peaks. The IR spectra with OH-stretching, deformation of $H_2O$and ${SO_4}^{2-}$stretching vibration include the existence of gypsum, ferrohexahydrite and quenstedetite in the precipitated and evaporite materials. In the SEM and EDS analysis for the evaporite material, gypsum with well-crystallized, acicular, and columnar form was distinctly observed.