• 한국정밀공학회지
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• 제11권1호
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• pp.138-149
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• 1994

This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

• Structural Engineering and Mechanics
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• 제25권5호
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• pp.577-596
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• 2007

Recent development of fiber optic sensor technology has provided an excellent choice for civil engineers for performance monitoring of civil infrastructures. Fiber optic sensors have the advantages of small dimensions, good resolution and accuracy, as well as excellent ability to transmit signal at long distances. They are also immune to electromagnetic and radio frequency interference and may incorporate a series of interrogated sensors multiplexed along a single fiber. These advantages make fiber optic sensors a better method than traditional damage detection methods and devices to some extent. This paper provides a review of recent developments in fiber optic sensor technology as well as some applications of fiber optic sensors to the performance monitoring of civil infrastructures such as buildings, bridges, pavements, dams, pipelines, tunnels, piles, etc. Existing problems of fiber optic sensors with their applications to civil structural performance monitoring are also discussed.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2565-2568
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• 2003

This paper presents a behavioral data monitoring system based on WAP(wireless application protocol) service for the 24-hour continuous health state monitoring of the elderly and the disabled. The developed system transmits a character message to the predefined mobile cell phone through SMS service when an emergency state takes place. Simultaneously, the image captured by a CCD camera is transmitted to the server computer installed WAP service program. Then, the user of the cell phone who received he message can access the server and open the transmitted image. This system can be used for the effective health monitoring of the elderly and disabled.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.328-332
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• 1996

The compressor is one of important elements in refrigerator cycle and play an important role of refrigeration efficiency and quality. Therefore it is very important to monitor state of normal and abnormal compressor. In this research, technic of AE is used for monitoring abnormal rotary compressor and an AE parameter which is a most proper parameter to monitor the abnormal state of compressor is determined by signal processing, Finally, the monitoring result of rotary compressor is agreement with the result of life test.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.473-475
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• 2001

We report the state of the development of monitoring system for 72.5kV GIS. In the first, the usual outline of the monitoring and diagnostic system for GIS was mentioned, and the detailed specifications and state of development were also described. Especially, we present items of monitoring for GIS such as the operating counter of CB, the leakage condition of $SF_6$ gas, the surge counter of LA and the leakage current of LA.

• Geomechanics and Engineering
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• 제11권4호
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• pp.571-585
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• 2016

The crest of the Pubugou central core rockfill dam (CCRD) cracked in the first and second impounding periods. To evaluate the safety of the Pubugou CCRD, an inversion analysis of the constitutive model parameters for rockfill materials is performed based on the in situ deformation monitoring data. The aim of this work is to truly reflect the deformation state of the Pubugou CCRD and determine the causes of the dam crest cracks. A novel real-coded genetic algorithm based upon the differences in gene fragments (DGFX) is proposed. It is used in combination with the radial based function neural network (RBFNN) to perform the parameters back analysis. The simulated settlements show good agreements with the monitoring data, illustrating that the back analysis is reasonable and accurate. Furthermore, the deformation gradient of the dam crest has been analysed. The dam crest has a great possibility of cracking due to the uncoordinated deformation, which agrees well with the field investigation. The deformation gradient decreases to the value lower than the critical one and reaches a stable state after the second full reservoir.

• International Journal of Contents
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• 제3권1호
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• pp.24-28
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• 2007

This paper embodies the agent based cinder monitoring system which supports PDA(Personal Digital Assistant). Monitoring system automatically manages data by using data managing agents such as a state managing agent, a location managing agent, a badness managing agent, a circumstances managing agent, etc, and uses a massive data processing agent to manage massive data. The development of agent based data monitoring system for the stable cinder reuse will be an epoch-making method to develop the process mechanized or manual-labored that widely spreads into the real-time automated process.

• International Journal of Contents
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• 제4권4호
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• pp.7-11
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• 2008

This paper embodies the agent based cinder monitoring system which supports PDA{Personal Digital Assistant). Monitoring system automatically manages data by using data managing agents such as a state managing agent, a location managing agent, a badness managing agent, a circumstances managing agent, etc, and uses a massive data processing agent to manage massive data. The development of agent based data monitoring system for the stable cinder reuse will be an epoch-making method to develop the process mechanized or manual-labored that widely spreads into the real-time automated process.

• 한국구조물진단유지관리공학회 논문집
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• 제16권1호
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• pp.99-109
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• 2012

이 연구에서는 변형률계를 사용하여 변위를 추정하는 이론식을 제안 및 검증하고 하중 작용점과 크기를 추정하여 강재보의 건전도 평가 시스템을 개발하고자 하였다. 실험결과 160kN(항복하중의 56%)가력시 최대처짐 점에서 변형률계를 사용하여 얻는 처짐과 변위계의 측정처짐과의 오차율이 2%이내로 나타났으며 하중작용점 및 크기의 추정도 오차율1% 이내로 나타났다. 이를 통해 변형률계로 강재보의 변위 및 하중을 계측 할 수 있으며 나아가 변위계와 하중계의 생략으로 경제적인 센서설계를 할 수 있다. Lab VIEW로 구현된 건전도 평가 프로그램은 측정된 데이터가 일정 범위(강도 한계상태, 사용성 한계상태, 항복변형률)를 넘어설 때 단계별 경고를 발생하였고 변형률계 만으로 사용성한계상태와 강도한계상태를 동시에 모니터링 할 수 있었다.

• Geomechanics and Engineering
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• 제17권4호
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• pp.375-383
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• 2019

In underground retreating longwall coal mining, hard roof collapse is one of the most challenging safety problems for mined-out areas. Identifying precursors for hard roof collapse is of great importance for the development of warning systems related to collapse geohazards and ground control. In this case study, the Xinhe mine was chosen because it is a standard mine and the minable coal seam usually lies beneath hard strata. Real-time monitoring of hard roof collapse was performed in longwall face 5301 of the Xinhe mine using support resistance and microseismic (MS) monitoring; five hard roof collapse cases were identified. To reveal the characteristics of MS activity during hard roof collapse development and to identify its precursors, the change in MS parameters, such as MS event rate, energy release, bursting strain energy, b value and the relationships with hard roof collapse, were studied. This research indicates that some MS parameters showed irregularity before hard roof collapse. For the Xinhe coalmine, a substantial decrease in b value and a rapid increase in MS event rate were reliable hard roof collapse precursors. It is suggested that the b value has the highest predictive sensitivity, and the MS event rate has the second highest.