• Journal of Electrical Engineering and Technology
• /
• 제8권3호
• /
• pp.572-580
• /
• 2013

Power metering and monitoring system is a basic element of Smart Grid technology. This paper proposes a new Non-Intrusive Load Monitoring (NILM) method for a residential buildings sector using the measured total active power consumption. Home electrical appliances are classified by ON/OFF state models, Multi-state models, and Composite models according to their operational characteristics observed by experiments. In order to disaggregate the operation and the power consumption of each model, an algorithm which includes a switching function, a truth table matrix, and a matching process is presented. Typical profiles of each appliances and disaggregation results are shown and classified. To improve the accuracy, a Time Lagging (TL) algorithm and a Permanent-On model (PO) algorithm are additionally proposed. The method is validated as comparing the simulation results to the experimental ones with high accuracy.

• 한국항공우주학회지
• /
• 제45권8호
• /
• pp.639-646
• /
• 2017

본 논문에서는 군용 항공기를 위한 새로운 하중 모니터링 시스템에 대하여 소개하였다. 이 시스템은 항공기에 장착되는 센서와 탑재장비 및 지상에서 운용되는 지상분석장비로 구성된다. 이 시스템을 이용하여 항공기에 작용하는 구조정적하중을 비행파라미터로 추정할 수 있을 뿐 아니라, 정적하중, 동적하중 및 예상치 못한 이벤트에 의한 구조물의 응답을 센서로 측정할 수 있다. 특히 다점 측정이 가능한 광섬유 센서를 사용하였다. 탑재장비는 관련 군사규격서의 요구도를 만족하도록 설계되었으며, 일련의 환경시험으로 입증하였다. 본 시스템은 비행시험에 앞서 지상구조시험에 사용되고 평가되었으며, 향후 비행시험평가를 통하여 군용 항공기의 구조하중 모니터링 시스템으로 사용될 예정이다.

• Smart Structures and Systems
• /
• 제6권3호
• /
• pp.183-196
• /
• 2010

Monitoring and economical design of alternative energy generators such as wind turbines is becoming increasingly critical; however acquisition of the dynamic output data can be a time-consuming and costly process. In recent years, low-cost wireless sensors have emerged as an enabling technology for structural monitoring applications. In this study, wireless sensor networks are installed in three operational turbines in order to demonstrate their efficacy in this unique operational environment. The objectives of the first installation are to verify that vibrational (acceleration) data can be collected and transmitted within a turbine tower and that it is comparable to data collected using a traditional tethered system. In the second instrumentation, the wireless network includes strain gauges at the base of the structure. Also, data is collected regarding the performance of the wireless communication channels within the tower. In both turbines, collected wireless sensor data is used for off-line, output-only modal analysis of the ambiently (wind) excited turbine towers. The final installation is on a turbine with embedded braking capabilities within the nacelle to generate an "impulse-like" load at the top of the tower. This ability to apply such a load improves the modal analysis results obtained in cases where ambient excitation fails to be sufficiently broad-band or white. The improved loading allows for computation of true mode shapes, a necessary precursor to many conditional monitoring techniques.

• Smart Structures and Systems
• /
• 제33권3호
• /
• pp.189-199
• /
• 2024

To properly extract the strain components under varying operational conditions is very important in bridge health monitoring. The abnormal sensor readings can be correctly identified and the expected operational performance of the bridge can be better understood if each strain components can be accurately quantified. In this study, strain components under varying load conditions, i.e., temperature variation and live-load variation are evaluated based on field strain measurements collected from a real concrete box-girder bridge. Temperature-induced strain is mainly regarded as the trend variation along with the ambient temperature, thus a smoothing technique based on the wavelet packet decomposition method is proposed to estimate the temperature-induced strain. However, how to effectively extract the vehicle-induced strain is always troublesome because conventional threshold setting-based methods cease to function: if the threshold is set too large, the minor response will be ignored, and if too small, noise will be introduced. Therefore, an autoencoder framework is proposed to evaluate the vehicle-induced strain. After the elimination of temperature and vehicle-induced strain, the left of which, defined as the model error, is used to assess the operational performance of the bridge. As empirical techniques fail to detect the degraded state of the structure, a clustering technique based on Gaussian Mixture Model is employed to identify the damage occurrence and the validity is verified in a simulation study.

• Smart Structures and Systems
• /
• 제16권3호
• /
• pp.435-457
• /
• 2015

The most widely known form of multifunctional aircraft structure is smart structures for structural health monitoring (SHM). The aim is to provide automated systems whose purposes are to identify and to characterize possible damage within structures by using a network of actuators and sensors. Unfortunately, environmental and operational variability render many of the proposed damage detection methods difficult to successfully be applied. In this paper, an original robust damage detection approach using output-only vibration data is proposed. It is based on independent component analysis and matrix perturbation analysis, where an analytical threshold is proposed to get rid of statistical assumptions usually performed in damage detection approach. The effectiveness of the proposed SHM method is demonstrated numerically using finite element simulations and experimentally through a conformal load-bearing antenna structure and composite plates instrumented with piezoelectric ceramic materials.

• Smart Structures and Systems
• /
• 제20권3호
• /
• pp.385-396
• /
• 2017

The recent advancements in sensing technologies allow us to record measurements from target structures at multiple locations and with relatively high spatial resolution. Such measurements can be used to develop data-driven methodologies for condition assessment, control, and health monitoring of target structures. One of the state-of-the-art technologies, Fiber Optic Strain Sensors (FOSS), is developed at NASA Armstrong Flight Research Center, and is based on Fiber Bragg Grating (FBG) sensors. These strain sensors are accurate, lightweight, and can provide almost continuous strain-field measurements along the length of the fiber. The strain measurements can then be used for real-time shape-sensing and operational load-estimation of complex structural systems. While several works have demonstrated the successful implementation of FOSS on large-scale real-life aerospace structures (i.e., airplane wings), there is paucity of studies in the literature that have investigated the potential of extending the application of FOSS into civil structures (e.g., tall buildings, bridges, etc.). This work assesses the feasibility of using FOSS to predict operational loads (e.g., wind loads) on chain-like structures. A thorough investigation is performed using analytical, computational, and experimental models of a 4-story steel building test specimen, developed at the University of Southern California. This study provides guidelines on the implementation of the FOSS technology on building-like structures, addresses the associated technical challenges, and suggests potential modifications to a load-estimation algorithm, to achieve a robust methodology for predicting operational loads using strain-field measurements.

• Smart Structures and Systems
• /
• 제24권5호
• /
• pp.617-630
• /
• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.992-995
• /
• 1996

The major roles of Power SCADA System are continuous monitoring of electrical equipments state, real-time data processing and dispatching. Especially, SCADA system demands fast response time in heavy load condition, high reliability, fault tolerance, expansion capacity for the future. According to developing computer system technology, SCADA system is changing system configuration from centralized processing system to distributed processing system. This paper describes operational benefits, problems and improvement (which is studying in theory) in the application of Open System Architecture SCADA which has been installed since 1994, Seoul regional control center in KEPCO.

• International Journal of Naval Architecture and Ocean Engineering
• /
• 제8권5호
• /
• pp.511-518
• /
• 2016

The dynamic positioning system (DPS) maintains an offshore vessel's position and heading under various environmental conditions by using its own thrust. DPS is regarded as one of the most important systems in offshore vessels. So, efficient operation and maintenance of the DPS are important issues. To monitor the DPS, it is necessary to define an appropriate key performance indicator (KPI) that can express the condition of the DPS from the perspective of operational efficiency and maintenance. In this study, a new KPI for the DPS is proposed considering the efficiency of the machinery and controller, the energy efficiency, and the environmental conditions in which the DPS is operated. The KPI is defined as a function of control deviation, energy consumption, and environmental load. A normalization factor is used to normalize the effect of environmental load on the KPI. The KPI value is calculated from DPS simulation and model test data. The possibility of applying the KPI to monitoring of DPS condition is discussed by comparing the values. The result indicates the feasibility of the new KPI.

• 한국물환경학회지
• /
• 제39권4호
• /
• pp.343-355
• /
• 2023

After the implementation of the total pollution load control system, the effect of improving river water quality by expanding investments in basic environmental facilities, inducing operational efficiency, and reducing the load of various pollutants was clear. However, since the implementation of the system, the management of non-point pollutants has been neglected; management focused on specific substances (biochemical oxygen demand (BOD) and total phosphorus (T-P)) and lacked specific cause analysis and action plans, failed to establish a relationship between water quality and pollution load, failed to reflect stakeholder demands for river water quality management, and failed to apply technical conditions. Therefore, to overcome the limitations raised and achieve a practical and efficient advanced total pollution system, the current system was partially improved and will continue to be improved. This study analyzed the performance and limitations of the total pollution system and introduced recent improvements and the contents that are being improved. The main contents included reducing emissions and reduction monitoring, using water quality tele-monitoring system (TMS) data and self-measurement data, adding population-inducing facilities, and adjusting regional development projects from 20 to 30 multi-family housing units, currentizing each pollutant source according to the roadmap. If the system is improved in a developmental direction and responds to various changes, it will be a more practical and effective policy.