• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.413-418
• /
• 1998

We often use induction motor in the hard environment including vibration and high ambient temperature, or in maintenance free operation, because induction motor has durable and simple structure. However, when we use it as servo actuator or accurate speed control motor, we have to equip sensor such as encoder and tachogenerator with the motor control system. And generally those sensor's abilities against bad environment are less than the induction motor itself, So if we can remove these sensors from the system, it'll have more environmental resistance, and the cost will also be reduced. Actually this removal has been achieved in limited field. However, that needs complex calculations and a certain elapse time for data processing. In our study, we intended to estimate the rotational speed from the motor current instead of speed sensor, easily and rapidly in comparison to former methods.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2010.04a
• /
• pp.787-790
• /
• 2010

현재 고속도로 상의 노후 교량에 대하여는 재하시험을 통하여 정량적인 내하력 평가를 수행하고, 만족스러운 수준의 내하력이 확보되지 않은 경우에는 보수, 보강 또는 교체를 수행한다. 그러나 교통량이 많은 고속도로사의 교량에 대해서는 재하시험이 매우 어렵고, 센서 케이블 작업으로 인하여 작업성이 떨어지는 경우가 많다. 본 연구에서는 이러한 문제점들을 개선하기 위하여 상시교통하중에 의한 교량 내하력 평가 시스템에 대한 연구를 수행하였다. 내하력 평가 대상 교량에 대하여 상시진동계측을 수행하였으며, 계측된 데이터를 통하여 교량의 동특성을 추정하였다. 추정된 동특성을 바탕으로 초기 해석 모델을 Downhill Simplex 방법을 이용하여 개선하였으며, 개선된 교량 모델을 이용하여 재하시험을 시뮬레이션 함으로써, 처짐 보정 계수를 구하였다.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2010.04a
• /
• pp.696-699
• /
• 2010

원자력 발전소의 격납건물은 인위적 또는 자연적 재해로부터 방사능의 외부누출을 방지함으로써 공중을 보호하는 역할을 하기 때문에 지속적인 건전성 확인을 통해 안전을 확보하는 것이 필수적이다. 격납건물의 구조적 건전성 확인은 통상 주기적으로 콘크리트에 대한 비파괴강도, 균열 및 중성화, 프리스트레스 텐던의 유효 긴장력 등의 측정을 통해 수행되고 있으나, 이러한 검사는 국부적인 건전도 정보만을 제공할 뿐 격납건물과 같은 대형 구조물 전체의 건전성에 대한 신뢰성 있는 평가 결과를 얻는데 많은 시간과 경비가 소요된다는 단점이 있다. 이러한 단점은 최근 구조물 전체의 상태를 평가하는 방법으로 주목받고 있는 구조건전성모니터링(Structural Health Monitoring, SHM)기법을 이용하여 극복할 수 있다. 본 논문에서는 실제 운전 중인 격납건물을 대상으로 상시진동 측정을 수행하였으며, SHM 기법의 기초자료로 활용될 수 있는 동적특성, 즉 격납건물의 고유진동수와 모드형상을 제시하였다.

• Structural Engineering and Mechanics
• /
• v.19 no.2
• /
• pp.123-139
• /
• 2005

An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm for identifying modal properties from continuous ambient vibration measurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers permanently installed on the cable-stayed Ting Kau Bridge. With the continuously identified results, variability in modal vectors due to varying environmental conditions and measurement errors is observed. Such an observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring use.

• Smart Structures and Systems
• /
• v.6 no.5_6
• /
• pp.525-543
• /
• 2010

Testing and validation processes are critical tasks in developing a new hardware platform based on a new technology. This paper describes a series of experiments to evaluate the performance of a newly developed MEMS-based wireless sensor node as part of a wireless sensor network (WSN). The sensor node consists of a sensor board with four accelerometers, a thermometer and filtering and digitization units, and a MICAz mote for control, local computation and communication. The experiments include calibration and linearity tests for all sensor channels on the sensor boards, dynamic range tests to evaluate their performance when subjected to varying excitation, noise characteristic tests to quantify the noise floor of the sensor board, and temperature tests to study the behavior of the sensors under changing temperature profiles. The paper also describes a large-scale deployment of the WSN on a long-span suspension bridge, which lasted over three months and continuously collected ambient vibration and temperature data on the bridge. Statistical modal properties of a bridge tower are presented and compared with similar estimates from a previous deployment of sensors on the bridge and finite element models.

• Smart Structures and Systems
• /
• v.15 no.3
• /
• pp.683-698
• /
• 2015

Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

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

• Steel and Composite Structures
• /
• v.27 no.3
• /
• pp.327-335
• /
• 2018

This paper presents structural assessment of a steel railway bridge for current condition using modal parameter to upgrade finite element modeling in order to gather accurate result. An adequate monitoring, such as acceleration, displacement, strain monitoring, is important tool to understand behavior and to assess structural performance of the structure under surround vibration by means of the dynamic analysis. Evaluation of conditions of an existing steel railway bridge consist of 4 decks, three of them are 14 m, one of them is 9.7 m, was performed with a numerical analysis and a series of dynamic tests. Numerical analysis was performed implementing finite element model of the bridge using SAP2000 software. Dynamic tests were performed by collecting acceleration data caused by surrounding vibrations and dynamic analysis is performed by Operational Modal Analysis (OMA) using collected acceleration data. The acceleration response of the steel bridge is assumed to be governing response quantity for structural assessment and provide valuable information about the current statute of the structure. Modal identification determined based on response of the structure play significant role for upgrading finite element model of the structure and helping structural evaluation. Numerical and experimental dynamic properties are compared and finite element model of the bridge is updated by changing of material properties to reduce the differences between the results. In this paper, an existing steel railway bridge with four spans is evaluated by finite element model improved using operational modal analysis. Structural analysis performed for the bridge both for original and calibrated models, and results are compared. It is demonstrated that differences in natural frequencies are reduced between 0.2% to 5% by calibrating finite element modeling and stiffness properties.

• Smart Structures and Systems
• /
• v.6 no.5_6
• /
• pp.579-593
• /
• 2010

Low-power radio frequency (RF) chip transceiver technology and the associated structural health monitoring platforms have matured recently to enable high-rate, lossless transmission of measurement data across large-scale sensor networks. The intrinsic value of these advanced capabilities is the allowance for high-quality, rapid operational modal analysis of in-service structures using distributed accelerometers to experimentally characterize the dynamic response. From the analysis afforded through these dynamic data sets, structural identification techniques can then be utilized to develop a well calibrated finite element (FE) model of the structure for baseline development, extended analytical structural evaluation, and load response assessment. This paper presents a case study in which operational modal analysis is performed on a three-span prestressed reinforced concrete bridge using a wireless sensor network. The low-power wireless platform deployed supported a high-rate, lossless transmission protocol enabling real-time remote acquisition of the vibration response as recorded by twenty-nine accelerometers at a 256 Sps sampling rate. Several instrumentation layouts were utilized to assess the global multi-span response using a stationary sensor array as well as the spatially refined response of a single span using roving sensors and reference-based techniques. Subsequent structural identification using FE modeling and iterative updating through comparison with the experimental analysis is then documented to demonstrate the inherent value in dynamic response measurement across structural systems using high-rate wireless sensor networks.

• Structural Monitoring and Maintenance
• /
• v.2 no.1
• /
• pp.1-18
• /
• 2015

Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Caraj$\acute{a}$s railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.