• The Journal of Engineering Geology
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• v.17 no.3
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• pp.339-350
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• 2007

Content, swelling, concentration, drainage of clay are critical factors that could control rock failures as well as discontinuous geological structures like faults and joints. Especially, the proportional components of clay minerals can be one of few direct indicators to a rock failure caused well by rainfall. Criticality of the role of clay mineral contents gets bigger in the slope and tunnel design. This study, using a horizontal boring core of pelitic/psammitic phyllite from the OO tunnel construction site, aims to investigate mineral composition changes related to fault distribution and their mechanical effects to the activity of these discontinuous layers (i.e., clay-filled fault layers), and eventually to define correlation among rock compositions, weathering products and rock instabilities. Field survey and lab tests were carried out for the composition and strength index of fault clay minerals within the core samples and microscopic analysis of fresh and weathered rock samples.

• 한국초전도학회:학술대회논문집
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• 2007.07a
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• pp.12-12
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• 2007

• Tunnel and Underground Space
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• v.11 no.3
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• pp.257-269
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• 2001

Numerical simulation is performed to understand the structural behavior of an underground radwaste repository, assumed to be located at the depth of 500 m, in a granitic rock mats, in which a fault intersects the roof of the repository cavern. Two dimensional universal distinct element code, UDEC is used in the analysis. The numerical model includes a granitic rock mass, a canister with PWR spent fuels surrounded by the compacted bentonite inside the deposition hole, and the mixed bentonite backfilled in the rest of the space within the repository cavern. The structural behavior of three different cases, each case with a fault of an angle of $33^{\circ},\;45^{\circ},\;and\;58^{\circ}$ passing through the cavern roof-wall intersection, has been compared. And then fro the case with the $45^{\circ}$ fault, the hydro-mechanical, thermo-mechanical, and thermo-hydro-mechanical interaction behavior have been studied. The effect of the time-dependent decaying heat, from the radioactive materials in PWR spent fuels, on the repository and its surroundings has been studied. The groundwater table is assumed to be located 10m below the ground surface, and a steady state flow algorithm is used.

• Proceedings of the SAREK Conference
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• 2004.11a
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• pp.86-86
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• 2004

• Proceedings of the SAREK Conference
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• 2003.07a
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• pp.172-172
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• 2003

• Proceedings of the SAREK Conference
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• 2004.06a
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• pp.144-144
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• 2004

• Smart Structures and Systems
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• v.5 no.2
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• pp.153-171
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• 2009

In this paper, the analytical fault detection and diagnosis (FDD) is presented using model-based and signal-based methodology with wavelet analysis on signals obtained from sensors and sensor networks. In the model-based FDD, we present the modeling of contact interface found in soft materials, including the biomedical contacts. Fingerprint analysis and signal-based FDD are also presented with an experimental framework consisting of a mechanical pneumatic system typically found in manufacturing automation. This diagnosis system focuses on the signal-based approach which employs multi-resolution wavelet decomposition of various sensor signals such as pressure, flow rate, etc., to determine leak configuration. Pattern recognition technique and analytical vectorized maps are developed to diagnose an unknown leakage based on the established FDD information using the affine mapping. Experimental studies and analysis are presented to illustrate the FDD methodology. Both model-based and wavelet-based FDD applied in contact interface and manufacturing automation have implication towards better quality of life by applying theory and practice to understand how effective diagnosis can be made using intelligent FDD. As an illustration, a model-based contact surface technology an benefit the diabetes with the detection of abnormal contact patterns that may result in ulceration if not detected and treated in time, thus, improving the quality of life of the patients. Ultimately, effective diagnosis using FDD with wavelet analysis, whether it is employed in biomedical applications or manufacturing automation, can have impacts on improving our quality of life.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.515-522
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• 2021

In this paper, we present and analyze a method of applying a machine learning to ultrasonic test signals for constant monitoring of the welding faults in a tubular steel tower. For the machine learning, feature selection based on genetic algorithm and fault signal classification using a support vector machine have been used. In the feature selection, the peak value, histogram lower bound, and normal negative log-likelihood from 30 features are selected. Those features clearly indicate the difference of signals according to the depth of faults. In addition, as a result of applying the selected features to the support vector machine, it has been possible to perfectly distinguish between the regions with and without faults. Hence, it is expected that the results of this study will be useful in the development of an early detection system for fault growth based on ultrasonic signals and in the energy transmission related industries in the future.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.1-14
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• 2024

Global navigation satellite system (GNSS) providing position, navigation and timing (PNT) services consist of satellite, ground, and user systems. Monitoring stations, a key element of the ground segment, play a crucial role in continuously collecting satellite navigation signals for service provision and fault detection. These stations detect anomalies such as threats to the signal-in-space (SIS) of satellites, receiver issues, and local threats. They deliver received data and detection results to the master station. This paper introduces the main monitoring algorithms and measurement pre-processing processes for quality assessment and fault detection of received satellite signals in current satellite navigation system monitoring stations. Furthermore, it proposes a strategy for the development of components, architecture, and algorithms for the new regional navigation satellite system (RNSS) monitoring stations.

• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1529-1543
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• 2005

Recently an unmanned aerial vehicle (UAV) has been widely used for military and civil applications. The role of a navigation system in the UAV is to provide navigation data to the flight control computer (FCC) for guidance and control. Since performance of the FCC is highly reliant on the navigation data, a fault in the navigation system may lead to a disastrous failure of the whole UAV. Therefore, the navigation system should possess a fault detection and isolation (FDI) algorithm. This paper proposes an attitude determination GPS/INS integrated navigation system with an FDI algorithm for a UAV. Hardware for the proposed navigation system has been developed. The developed hardware comprises a commercial inertial measurement unit (IMU) and the integrated navigation package (INP) which includes an attitude determination GPS (ADGPS) receiver and a navigation computer unit (NCU). The navigation algorithm was implemented in a real-time operating system with a multi-tasking structure. To evaluate performance of the proposed navigation system, a flight test has been performed using a small aircraft. The test results show that the proposed navigation system can give accurate navigation results even in a high dynamic environment.