• 품질경영학회지
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• 제51권2호
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• pp.315-327
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• 2023

Purpose: Recently, research has continued to predict the time of failure of the facility through measurement data obtained by attaching a sensor to the facility. However, depending on the facility, it may be difficult to attach a sensor. The purpose of this study is to propose a power generation maintenance plan system based on failure record data obtained from Continuous Ship Unloader, one of the facilities that is difficult to attach sensors. Methods: This study uses data collected from 2012 to 2022 from the 'CSU-1B' model among Continuous Ship Unloader operated by Korea Midland Power Co., LTD. By fitting fault record data to the Weibull distribution, appropriate maintenance cycles and ranges for each target facility subsystem are derived. In addition, maintenance group between subsystems is selected through Euclidean distance, a metric often used for time series data similarity. Through this, a system for establishing an maintenance plan for power generation facilities is proposed. Results: The results of this study are as follows. For the 17 subsystems of the Continuous Ship Unloader, proper maintenance cycles and ranges were determined, and a total of four maintenance groups were chosen. This resulted in the creation of an power generation maintenance plan system and the establishment of an maintenance plan. Conclusion: This study is a case study of power generation facilities. We proposed a maintenance plan system for Continuous Ship Unloader among power generation facilities.

• 한국컴퓨터정보학회논문지
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• 제22권2호
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• pp.9-19
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• 2017

Useful continuous sensing applications are increasingly emerging as a new class of mobile applications. Meanwhile, open, multi-use sensor devices are newly adopted beyond smartphones, and provide huge opportunities to expand potential application categories. In this upcoming environment, uncoordinated use of sensor devices would cause severe imbalance in power consumption of devices, and thus result in early shutdown of some sensing applications depending on power-hungry devices. In this paper, we propose EnergyCordy, a novel inter-device energy use coordination system; with a system-wide holistic view, it coordinates the energy use of concurrent sensing applications over multiple sensor devices. As its key approach, we propose a relaxed sensor association; it decouples the energy use of an application from specific sensor devices leveraging multiple context inference alternatives, allowing flexible energy coordination at runtime. We demonstrated the effectiveness of EnergyCordy by developing multiple example applications over custom-designed wearable senor devices. We show that EnergyCordy effectively coordinates the power usage of concurrent sensing applications over multiple devices and prevent undesired early shutdown of applications.

• 센서학회지
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• 제23권6호
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• pp.402-408
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• 2014

Heart rate is one of the most important signal to monitor the health condition of the patient or exerciser. Various wearable devices have been developed for the continuous monitoring of ECG signal from human body during exercise. Among these, ECG chest belt has been widely used. However wearing chest belt with ECG sensor is uncomfortable in normal life due to the electrode contact between metal electrodes of ECG sensor and skin of the human body. So we develop the royal healthcare backpack that can measure ECG signal without skin contact by using capacitor-type ECG sensor. The position of the measurement point is critical to collect a clear ECG signal in the capacitive ECG measurement from backpack. Various tests were conducted to find the optimal ECG measurement position which has less noise and could get strong and clear ECG signal during exercise, walking, hiking, mountain climbing and cycling.

• 비파괴검사학회지
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• 제27권6호
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• pp.483-500
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• 2007

Emerging sensor-based structural health monitoring (SHM) technology can play an important role in inspecting and securing the safety of aging civil infrastructure, a worldwide problem. However, implementation of SHM in civil infrastructure faces a significant challenge due to the lack of suitable sensors and reliable methods for interpreting sensor data. This paper reviews recent efforts and advances made in addressing this challenge, with example sensor hardware and software developed in the author's research center. It is proposed to integrate real-time continuous monitoring using on structure sensors for global structural integrity evaluation with targeted NDE inspection for local damage assessment.

• 한국정보과학회논문지:데이타베이스
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• 제36권4호
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• pp.280-291
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• 2009

스카이라인 질의 처리는 센서 네트워크 응용에서 다차원 데이터를 효과적으로 활용할 수 있어서 그 역할이 중요하다. 센서 네트워크는 배터리 제약 사항을 가지고 있기 때문에, 센서 네트워크에서의 스카이라인에 관한 연구는 에너지 소비를 최소화 하는데 그 목표를 두고 있다. 이를 위해 기존연구에서 필터링 기법이 제안되었다. 하지만 기존 필터링 기법은 일회성 질의에 초점을 맞추고 있고, 상위 노드의 정보만을 활용하기 때문에 그 성능의 한계가 있다. 본 논문에서는 연속스카이라인 질의 처리를 위한 상향식 필터링 투플 선정 방법을 제안한다. 하위노드에서 생성된 이전 스카이라인 정보를 각 센서노드에 저장하고, 필터링 투플 선정에 활용함으로써 불필요한 데이터 통신을 감소시킬 수 있다, 이와 더불어 추가 필터링 투플을 선택할 때 사용될 수 있는 SFT(Support Filtering Tuple)방법을 제안한다. 센서 데이터의 경우, 이전 센싱된 데이터와 현재 데이터 간의 시간 관계성(temporal correlation)의 특징을 갖고 있다. SFT 방법은 저장된 과거 데이터를 기반으로 현재데이터를 예측하여 추가 필터링 투플을 선정하여 필터링 성능을 향상시킨다. 실험 결과를 통해, 제안하는 방법들이 기존 방법에 비해 데이터 감소율과 총 통신량 측면에서 효율적임을 보여준다.

• 한국컴퓨터정보학회논문지
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• 제16권5호
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• pp.135-145
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• 2011

오늘날 센서 기술의 발전 및 보급으로 인해 USN 기반의 실시간 모니터링 응용에서의 센서 데이터 처리 시스템에 대한 연구가 활발히 진행 되고 있다. 센서 데이터는 시간에 따라 빠르게 변화하고 연속적인 저수준 상태의 방대한 양의 데이터를 생성하는 특성을 갖는다. 하지만 엔드유저는 상대적으로 고수준 상태의 데이터에 관심이 있기 때문에 빠르게 변화하고 연속적인 대량의 저수준 센서 데이터를 효과적으로 처리하는 시스템이 필수적이다. 본 논문에서는 USN 기반의 화재감시 응용에서 OLAP(On-Line Analytical Processing) 기술을 이용한 다차원 분석 질의 처리 기능과 학습기반 분류기를 통한 이상치 탐지 기능을 제공하는 센서 데이터 처리 시스템을 제안한다. 실험 시나리오를 통해 우리의 센서 데이터 처리 시스템에 대한 타당성을 검증하며 실험에 필요한 다양한 센서 데이터는 자체 개발한 센서 데이터 생성기를 이용한다.

• 한국정보통신학회논문지
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• 제15권7호
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• pp.1525-1530
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• 2011

다양한 센서들로부터 실시간으로 수집되는 데이터를 분석, 처리해야하는 유비쿼터스 환경의 다양한 응용서비스(모니터링 서비스)를 개발하기 위해서는 반드시 연속질의 처리 방법이 요구된다. 기존 연구에서 연속질의는 대부분 간격질의와 영역질의만으로 표현되고, 이러한 질의에 대한 처리 기법들이 제시되었다. 그러나 연속질의의 종류는 매우 다양하며, 속성 조건, 공간 조건, 시간 조건의 결합을 통해 표현될 수 있다. 이 논문에서는 연속질의의 종류를 분류하고, 여러 조건들의 결합을 통해 표현 가능한 연속질의 모델을 제안하고자 한다. 이 논문은 연속질의를 표현하는 질의 모델을 제안함으로써, 연속질의 처리를 위한 다양한 후속 연구에 대한 방향을 제시하는데 기여하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.3-5
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• 2007

Many continuous queries are important to be process efficiently in a data stream environment. It is applied a query index technique that takes linear performance irrespective of the number and width of intervals for processing many continuous queries. Previous researches are not able to support the dynamic insertion and deletion to arrange intervals for constructing an index previously. It shows that the insertion and search performance is slowed by the number and width of interval inserted. Many intervals have to be inserted and searched linearly in a data stream environment. Therefore, we propose Hashed Multiple Lists in order to process continuous queries linearly. Proposed technique shows fast linear search performance. It can be utilized the systems applying a sensor network, and preprocessing technique of spatiotemporal data mining.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권4호
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• pp.1209-1223
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• 2022

Blood pressure is one of the key physiological parameters for determining human health, and can prove whether human cardiovascular function is healthy or not. In general, what we call blood pressure refers to arterial blood pressure. Blood pressure fluctuates greatly and, due to the influence of various factors, even varies with each heartbeat. Therefore, achievement of continuous blood pressure measurement is particularly important for more accurate diagnosis. It is difficult to achieve long-term continuous blood pressure monitoring with traditional measurement methods due to the continuous wear of measuring instruments. On the other hand, radar technology is not easily affected by environmental factors and is capable of strong penetration. In this study, by using machine learning, tried to develop a linear blood pressure prediction model using data from a public database. The radar sensor evaluates the measured object, obtains the pulse waveform data, calculates the pulse transmission time, and obtains the blood pressure data through linear model regression analysis. Confirm its availability to facilitate follow-up research, such as integrating other sensors, collecting temperature, heartbeat, respiratory pulse and other data, and seeking medical treatment in time in case of abnormalities.

• Journal of Mechanical Science and Technology
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• 제18권2호
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• pp.286-293
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• 2004

The air fuel ratios of current gasoline engines are almost controlled by several air flow meters. When CVVT (Continuous Variable Valve Timing) is applied to a gasoline engine for higher engine performance, the MAP (Manifold Absolute Pressure) sensor is difficult to follow the instantaneous air fuel ratio due to the valve timing effect. Therefore, a HFM (Hot Film Flow Meter) is widely used for measuring intake air flow in this case. However, the HFMs are incapable of indicating to reverse flow, the oscillation of intake air flow has an negative effect on the precision of the HFM. Consequently, the various duct configurations in front of the air flow sensor affect the precision of HFM sensitivity. This paper mainly focused on the analysis of the reverse flow, flow fluctuation in throttle upstream and the geometry of intake system which influence the HFM measurement.