• Structural Monitoring and Maintenance
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• 제6권3호
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• pp.219-235
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• 2019

Scheduled inspections of common crossings are one of the main cost drivers of railway maintenance. Prognostics and health management (PHM) approach and modern monitoring means offer many possibilities in the optimization of inspections and maintenance. The present paper deals with data driven prognosis of the common crossing remaining useful life (RUL) that is based on an inertial monitoring system. The problem of scheduled inspections system for common crossings is outlined and analysed. The proposed analysis of inertial signals with the maximal overlap discrete wavelet packet transform (MODWPT) and Shannon entropy (SE) estimates enable to extract the spectral features. The relevant features for the acceleration components are selected with application of Lasso (Least absolute shrinkage and selection operator) regularization. The features are fused with time domain information about the longitudinal position of wheels impact and train velocities by multivariate regression. The fused structural health (SH) indicator has a significant correlation to the lifetime of crossing. The RUL prognosis is performed on the linear degradation stochastic model with recursive Bayesian update. Prognosis testing metrics show the promising results for common crossing inspection scheduling improvement.

• Smart Structures and Systems
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• 제21권5호
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• pp.687-694
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• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.

• 한국터널지하공간학회 논문집
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• 제16권1호
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• pp.1-11
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• 2014

본 논문은 단선터널 라이닝의 최적 계측 측점수를 산정하기 위해 단순보 형태로 모델링하여 터널 라이닝 역해석 프로그램에 적용한 결과와 상용 프로그램에 적용한 결과를 상호 비교하여 평가하였다. 단선터널을 대상으로 터널 라이닝에 대칭 분포하중이 작용하는 경우와 비대칭 분포하중이 작용하는 경우로 가정하여 터널해석 시 널리 사용되는 상용 프로그램에 하중조건을 입력시켜 터널 라이닝의 단면 위치별 변위와 응력을 산출하였다. 산출된 변위를 계측 측점수 3점, 5점, 7점으로 터널 라이닝 역해석 프로그램에 입력시켜서 구한 응력과 변위를 비교하여 최적 계측 측점수를 산정하였다. 연구결과 실무적으로 계측 수행의 경제성과 터널 계측의 손망실률을 고려한 계측 측점수가 최소 5점은 되어야 할 것으로 판단된다.

• 전기학회논문지
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• 제63권6호
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• pp.850-854
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• 2014

Analyzing dynamic performance between pantograph and contact wire depends on mechanical and electrical conditions such as contact force, currents, aerodynamics of pantograph and tension of overhead contact wire. For the characteristic of dynamic performance between pantograph and overhead contact wire, various evaluation systems are used to measuring of the interaction of the contact line and the pantograph. Among the various methods, the contact force and percentage of arcing are intended to prove the safety and the quality of the current collection system on the train. However, these methods are only capable of measuring on the train which are installed measurement systems. Therefore in this paper, a track-side monitoring system was implemented to measure electrical characteristics from active overhead contact wire systems in order to constantly estimate current collection performance of railway operation. In addition, a method to analyze loss of contact phenomena was proposed. According to simulation results, the proposed system was capable of measuring abnormal electrical behavior of pantograph and contact wires on the track-side. The advantage of the proposed system is possible to detect loss of contact or any other electrical abnormalities of all types of trains within sections from sub to sub without the need to install any on-board equipment on trains.

• International Journal of Computer Science & Network Security
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• 제24권3호
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• pp.43-52
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• 2024

Health Monitoring System is a sophisticating technology and another way to the normal/regular management of the health of the patient. This Health Monitoring Mobile Application is a contribution from our side to the public and to the overall health industry in Pakistan. With the help of Health mobile application, the users will be able to store their medical records, prescriptions and retrieve them later. The users can store and keep track of their vital readings (heart rate, blood pressure, fasting glucose, random glucose). The mobile application also shows hospitals that are nearby in case the user wants to avail of any medical help. An important feature of the application is the symptoms-based disease prediction, the user selects the symptoms which he has and then the application will name certain diseases that match those symptoms based on relevant algorithms. The major advances and issues have been discussed, and as well as potential tasks to health monitoring will be identified and evaluated.

• 한국멀티미디어학회논문지
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• 제21권3호
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• pp.382-390
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• 2018

A major accident occurring on the bed is falls that occur during at times when the care of nurses or protectors is inadequate, which is fatal to patients or the elderly. In particular, Enuresis or sleepiness caused by sleep apnea increases the risk of falls. Therefore, it is very important to detect falls and sleep apnea of patients without infringing privacy in the bed to patient's safety and accident prevention. In this paper, we reviewed the technologies developed for bed monitoring and implemented a non-intrusive monitoring system. The Occupancy Sensor allows the temperature of the bed and surrounding area to be extracted to enable track of the patient's motion. The Doppler Radar detects the patient's movements at normal times and the respiration state when patients have no movement during sleeping. It is specially designed for real-time monitoring of falling and respiration during sleeping through contactless multi-sensing while solving patient's privacy problems.

• 한국산학기술학회논문지
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• 제18권1호
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• pp.609-617
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• 2017

철도는 전 세계적으로 매우 안전하고 중요한 운송 수단 중 하나이다. 그러나 철도시스템이 복잡도가 높아지고 주행거리 증가 등으로 인해 매년 사고가 지속적으로 발생하고 있다. 특히, 고속열차와 화물열차의 경우, 차축베어링 비정상 과열로 인하여 차축베어링의 기능이 소실되면 차축의 불균등한 하중을 초래한다. 따라서, 차축베어링의 비정상 과열은 심각한 사고 또는 차량 탈선의 원인이 될 수 있다. 이에 따라서 현재 고속열차 운행 중 차축의 비정상적인 발열을 검지하기 위하여 차축온도검지장치(Hot Box Detector, HBD)가 설치되어 운영되고 있다. 본 연구에서는 비정상 차축 과열 발생시, 이를 빠르고 효율적으로 검지하기 위하여 지수가중이동평균(EWMA) 기법을 적용한 차축온도 모니터링 방법을 제안하였다. 또한 제안한 방법에 대하여 통계적으로 설계하였다. 본 연구에서 제안하는 방법은 현재의 차축온도검지 모니터링 방법과 비교하여 비정상 과열의 발생에 대하여 더 좋은 성능으로 평가되었으며 그 수행도는 최대 170% 향상되었다.

• 헤리티지:역사와 과학
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• 제52권3호
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• pp.74-93
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• 2019

함안 용산리 함안층 새발자국 화석산지(천연기념물 제222호)에서는 Koreanaornis hamanensis와 Jindongornipes kimi로 명명된 두 종의 새발자국이 발견되었으며, 용각류 발자국과 생흔화석 Cochlichnus도 보고되었다. 특히 Koreanaornis hamanensis는 세계에서 두 번째로 기록된 새발자국 화석종으로 학술적 가치가 매우 뛰어나다. 이 일대는 구들장용 판석의 채석장이었으며, 1969년에 세계적 희귀 화석지로 알려지면서 크게 훼손되어, 현재는 지정 당시의 25% 정도가 잔존한다. 함안층은 경상누층군의 하양층군에 속하며 주로 적회색의 미사암과 흑색의 이암이 교호하는 암상을 보인다. 미사암과 이암의 경계는 점이적이며, 연흔과 건열 등의 퇴적 구조가 뚜렷하다. 연구 지역의 퇴적암은 퇴적순서와 구조 및 암상에 따라 총 7개의 지층으로 구분되며, 새발자국 화석은 최상부층에서 나타난다. 비파괴 손상도 평가 결과, 화학적 생물학적 손상은 7개 지층에서 모두 매우 낮게 나타났다. 물리적 손상도의 경우 박락 0.49%, 박리 0.04%, 탈락 0.28%로 매우 낮은 손상률을 보였다. 그러나 절리 등 불연속면의 균열지수는 6.20으로 비교적 높으며, 배면과 북서측의 표면은 하등생물의 피복이 심하여 지층의 단면을 중심으로 염에 의한 백화현상이 관찰된다. 화석산지의 초음파 물성은 전반적으로 중간풍화단계(MW)를 보였다. 특히 공룡발자국이 있는 남서측 부근이 상대적으로 신선하며, 보호각 기둥 주위로 풍화가 진전된 양상을 보였다. 이 화석산지에 발달한 불연속면은 5종류로서 가장 높은 점유율을 보이는 불연속면은 층리면이다. 평사투영으로 사면의 안정성을 분석한 결과, 평면 및 쐐기파괴에는 안정적이지만 전도파괴의 가능성이 있는 것으로 나타났다. 이 화석산지의 종합적인 손상 정도 및 안정성은 양호한 것으로 판단되나, 화석층의 물리화학적 풍화와 보호각 기둥과 접하는 모르타르의 백화현상 등은 제어하기 어려운 상태로 보여, 지속적인 모니터링과 보존처리 및 관리가 수행되어야 할 것이다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2002년도 학술발표회 논문집(I)
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.