• Title/Summary/Keyword: fault prediction

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Feature Extraction for Bearing Prognostics based on Frequency Energy (베어링 잔존 수명 예측을 위한 주파수 에너지 기반 특징신호 추출)

  • Kim, Seokgoo;Choi, Joo-Ho;An, Dawn
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.2
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    • pp.128-139
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    • 2017
  • Railway is one of the public transportation systems along with shipping and aviation. With the recent introduction of high speed train, its proportion is increasing rapidly, which results in the higher risk of catastrophic failures. The wheel bearing to support the train is one of the important components requiring higher reliability and safety in this aspect. Recently, many studies have been made under the name of prognostics and health management (PHM), for the purpose of fault diagnosis and failure prognosis of the bearing under operation. Among them, the most important step is to extract a feature that represents the fault status properly and is useful for accurate remaining life prediction. However, the conventional features have shown some limitations that make them less useful since they fluctuate over time even after the signal de-noising or do not show a distinct pattern of degradation which lack the monotonic trend over the cycles. In this study, a new method for feature extraction is proposed based on the observation of relative frequency energy shifting over the cycles, which is then converted into the feature using the information entropy. In order to demonstrate the method, traditional and new features are generated and compared using the bearing data named FEMTO which was provided by the FEMTO-ST institute for IEEE 2012 PHM Data Challenge competition.

Survey and Numerical Analysis Cases of Ground Subsidence by Mine Goaf (광산 채굴적으로 인한 지반침하 조사 및 해석 사례)

  • Hyun-Bae Park;Seong-Woo Moon;Sejeong Ju;Jeungeum Lee;Yong-Seok Seo
    • The Journal of Engineering Geology
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    • v.34 no.1
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    • pp.1-12
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    • 2024
  • South Korea's mining industry was actively developed until 1980, but subsequent declining profitability forced many mines to close. Most of the abandoned mines are susceptible to persistent subsidence because of the length of time since mining ceased. Accurate prediction of the locations and times of subsidence is difficult; therefore, this study aims to apply continuum analysis to past cases of subsidence to establish a method of predicting the location and magnitude of future subsidence. The study area is an area of ○○ mining located between the Yangsan fault zone and the Moryang fault zone, in which three subsidence events occurred between 2005 and 2009. Drilling surveys and electrical resistivity surveys were performed at subsidence sites determined the distribution of strata, and through laboratory tests obtained the physico-mechanical properties of the rock. Numerical analysis of the results found that the plastic status area includes the areas of actual subsidence and that continuum analysis can also be used to predict the location and magnitude of subsidence caused by mine goaf.

Prediction of ground-condition ahead of tunnel face using electromagnetic wave - analytical study (전자기파를 이용한 터널전방 예측 -해석기법 중심으로)

  • Choi, Jun-Su;Cho, Gye-Chun;Lee, Geun-Ha;Yoon, Ji-Nam
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.6 no.4
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    • pp.327-343
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    • 2004
  • During tunnel construction, ground failures often occur due to existence of weak zones, such as faults, joints, and cavities, ahead of tunnel face. It is hard to detect effectively weak zones, which can lead underground structure to fail after excavation and before supporting, by using conventional characterization methods. In this study, an enhanced analytical method of predicting weak zones ahead of tunnel face is developed to overcome some problems in the conventional geophysical exploration methods. The analytical method is based on Coulomb's and Gauss' laws with considering the characteristics of electric fields subjected to rock mass. Using the developed method, closed form solutions are obtained to detect a spherical shaped zone and an oriented fault ahead of tunnel face respectively. The analytical results suggest that the presence of weak zones and their sizes, location, and states can be accurately predicted by combining a proper inversion process with resistance measured from several electrodes on the tunnel face. It appears that the skin depth or resistivity in rock mass is affected by the diameter of tunnel face, natural electric potential and noises induced by experimental measurement and spatial distribution of uncertain properties. The developed analytical solution is verified through experimental tests. About 1800 concrete blocks of 5cm by 5cm by 5cm in size are prepared and used to model a joint rock mass around tunnel face. Weak zones are simulated ahead of tunnel face with a material which has relatively higher conductivity than concrete blocks. Experimental results on the model test show a good agreement with analytical results.

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Modeling of a PEM Fuel Cell Stack using Partial Least Squares and Artificial Neural Networks (부분최소자승법과 인공신경망을 이용한 고분자전해질 연료전지 스택의 모델링)

  • Han, In-Su;Shin, Hyun Khil
    • Korean Chemical Engineering Research
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    • v.53 no.2
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    • pp.236-242
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    • 2015
  • We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

The Application of GIS for the Prediction of Landslide-Potential Areas (산사태의 발생가능지 예측을 위한 GIS의 적용)

  • Lee, Jin-Duk;Yeon, Sang-Ho;Kim, Sung-Gil;Lee, Ho-Chan
    • Journal of the Korean Association of Geographic Information Studies
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    • v.5 no.1
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    • pp.38-47
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    • 2002
  • This paper demonstrates a regional analysis of landslide occurrence potential by applying geographic information system to the Kumi City selected as a pilot study area. The estimate criteria related to natural and humane environmental factors which affect landslides were first established. A slope map and a aspect map were extracted from DEM, which was generated from the contour layers of digital topographic maps, and a NDVI vegetation map and a land cover map were obtained through satellite image processing. After the spatial database was constructed, indexes of landslide occurrence potential were computed and then a few landslide-potential areas were extracted by an overlay method. It was ascertained that there are high landslide-potential at areas of about 30% incline, aspects including either south or east at least, adjacent to water areas or pointed end of the water system, in or near fault zones, covered with medium vegetable. For more synthetic and accurate analysis, soil data, forest data, underground water level data, meteorological data and so on should be added to the spatial database.

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A Study on the Development of integrated Process Safety Management System based on Artificial Intelligence (AI) (인공지능(AI) 기반 통합 공정안전관리 시스템 개발에 관한 연구)

  • KyungHyun Lee;RackJune Baek;WooSu Kim;HeeJeong Choi
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.403-409
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    • 2024
  • In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.

Study on Fire.Explosion Accidents Prediction Model Development of LPG Vaporizer (LPG 기화기의 화재.폭발사고 예측모델개발에 관한 연구)

  • Ko, Jae-Sun
    • Journal of the Korean Institute of Gas
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    • v.14 no.1
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    • pp.28-36
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    • 2010
  • We have garnered 3,593 data of gas accidents reported for 12 years from 1995, and then analyzed the LPG vaporizer accidents according to their types and causes based on the classified database. According to the results the gas rupture has been the most common accident followed by the release, explosion and then fire accidents, the most frequent accident-occurring sub-cause is LPG check floater faults. In addition, we have applied the Poisson Probability Functions to predict the most-likely probabilities of fire, explosion, release and rupture with the LPG vaporizer in the upcoming 5 years. In compliance with Poisson Probability Functions results, in the item which occurs below 3 "LPG-Vaporizer-Fire", in the item which occurs below 5 "LPG-Vaporizer-Products Faults-Check Floater" and the item which occurs below 10 appeared with "LPG-Vaporizer-Products Faults". From this research we have assured the successive database updating will highly improve the anticipating probability accuracy and thus it will play a key role as a significant safety- securing guideline against the gas disasters.

A Study on the Design of Database to Improve the Capability of Managing Offshore Wind Power Plant (해상풍력 풍력시스템의 관리능력 향상을 위한 데이터베이스 설계에 관한 연구)

  • Kim, Do-Hyung;Kim, Chang-Suk;Kyong, Nam-Ho
    • Journal of the Korean Solar Energy Society
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    • v.30 no.3
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    • pp.65-70
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    • 2010
  • As for the present wind power industry, most of the computerization for monitoring and control is based on the traditional development methodology, but it is necessary to improve SCADA system since it has a phenomenon of backlog accumulation in the applicable aspect of back-data as well as in the operational aspect in the future. Especially for a system like offshore wind power where a superintendent cannot reside, it is desirable to operate a remote control system. Therefore, it is essential to establish a monitoring system with appropriate control and monitoring inevitably premised on the integrity and independence of data. As a result, a study was carried out on the modeling of offshore wind power data-centered database. In this paper, a logical data modeling method was proposed and designed to establish the database of offshore wind power. In order for designing the logical data modeling of an offshore wind power system, this study carried out an analysis of design elements for the database of offshore wind power and described considerations and problems as well. Through a comparative analysis of the final database of the newly-designed off-shore wind power system against the existing SCADA System, this study proposed a new direction to bring about progress toward a smart wind power system, showing a possibility of a service-oriented smart wind power system, such as future prediction, hindrance-cause examination and fault analyses, through the database integrating various control signals, geographical information and data about surrounding environments.

Vulnerability Assessment Procedure for the Warship Including the Effect of Shotline and Penetration of Fragments (탄두의 관통 효과를 고려한 함정 취약성 평가 절차에 관한 기본 연구)

  • Kim, Kwang-Sik;Lee, Jang-Hyun
    • Journal of the Society of Naval Architects of Korea
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    • v.49 no.3
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    • pp.254-263
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    • 2012
  • The survivability of warship is assessed by susceptibility, vulnerability and recoverability. Essentially, a vulnerability assessment is a measure of the effectiveness of a warship to resist hostile weapon effects. Considering the shot line and its penetration effect on the warship, present study introduces the procedural aspects of vulnerability assessments of warship. Present study also considers the prediction of penetration damage to a target caused by the impact of projectiles. It reflects the interaction between the weapon and the target from a perspective of vulnerable area method and COVART model. The shotline and tracing calculation have been directly integrated into the vulnerability assessment method based on the penetration equation empirically obtained. A simplified geometric description of the desired target and specification of a threat type is incorporated with the penetration effect. This study describes how to expand the vulnerable area assessment method to the penetration effect. Finally, an example shows that the proposed method can provide the vulnerability parameters of the warship or its component under threat being hit through tracing the shotline path thereby enabling the vulnerability calculation. In addition, the proposed procedure enabling the calculation of the component's multi-hit vulnerability introduces a propulsion system in dealing with redundant Non-overlapping components.

A Cost-effective Control Flow Checking using Loop Detection and Prediction (루프 검출 및 예측 방법을 적용한 비용 효율적인 실시간 분기 흐름 검사 기법)

  • Kim Gunbae;Ahn Jin-Ho;Kang Sungho
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.42 no.12
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    • pp.91-102
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    • 2005
  • Recently, concurrent error detection for the processor becomes important. But it imposes too much overhead to adopt concurrent error detection capability on the system. In this paper, a new approach to resolve the problems of concurrent error detection is proposed. A loop detection scheme is introduced to reduce the repetitive loop iteration and memory access. To reduce the memory overheat an offset to calculate the target address of branching node is proposed. Performance evaluation shows that the new architecture has lower memory overhead and frequency of memory access than previous works. In addition, the new architecture provides the same error coverage and requires nearly constant memory size regardless of the size of the application program. Consequently, the proposed architecture can be used as an cost effective method to detect control flow errors in the commercial on the shelf products.