• Title/Summary/Keyword: 상태열화모델

Search Result 51, Processing Time 0.022 seconds

Development of the Deterioration Models for the Port Structures by the Multiple Regression Analysis and Markov Chain (다중 회귀분석 및 Markov Chain을 통한 항만시설물의 상태열화모델 개발)

  • Cha, Kyunghwa;Kim, Sung-Wook;Kim, Jung Hoon;Park, Mi-Yun;Kong, Jung Sik
    • Journal of the Computational Structural Engineering Institute of Korea
    • /
    • v.28 no.3
    • /
    • pp.229-239
    • /
    • 2015
  • In light of the significant increase in the quantities of goods transported and the development of the shipping industry, the frequency of usage of port structures has increased; yet, the government's budget for the shipping & port of SOC has been reduced. Port structures require systematically effective maintenance and management trends that address their growing frequency of usage. In order to construct a productive maintenance system, it is essential to develop deterioration models of port structures that consider various characteristics, such as location, type, use, constructed level, and state of maintenance. Processes for developing such deterioration models include examining factors that cause the structures to deteriorate, collecting data on deteriorating structures, and deciding methods of estimation. The techniques used for developing the deterioration models are multiple regression analysis and Markov chain theory. Multiple regression analysis can reflect changes over time and Markov chain theory can apply status changes based on a probabilistic method. Along with these processes, the deterioration models of open-type and gravity-type wharfs were suggested.

Design of System Diagnosis Insulation Degradation of Motor by using Electromagnetic Wave(1) (전자파를 이용한 전동기 절연열화 진단시스템의 설계(1))

  • Kim, Yi-Gon;Yoo, Kweon-Jong
    • Proceedings of the KIEE Conference
    • /
    • 2000.07d
    • /
    • pp.2531-2534
    • /
    • 2000
  • 본 연구는 전동기의 부분방전에 의해 발생되는 전자파를 측정하여 전동기의 열화상태를 진단할 수 있는 전동기 절연열화진단시스템을 설계하는 방법을 제안하고자 한다. 따라서 부분방전에 의한 전자파를 측정하는 시스템을 구성하고, 측정된 데이터를 분석하여 정량화된 특징 데이터를 추출하고 생성된 데이터를 이용한 뉴로-퍼지 진단모델설계 방법을 제시한다. 그리고 제안된 방법에 의해 설계된 진단모델을 실측데이터를 통해 진단하여 그 타당성을 입증하고자 한다. 1단계 연구로, 본 연구에서는 현장 전동기의 전자파를 On-Line으로 계측하는 시스템을 구성하여 전동기의 절연체내에서 발생하는 부분방전에 의한 전자파를 계측하여 데이터로부터 전동기의 절연열화상태를 해석하여 절연 열화와의 관계를 분석하였다.

  • PDF

Quantitative Deterioration and Maintenance Profiles of Typical Steel Bridges based on Response Surface Method (응답면 기법을 이용한 강교의 열화 및 보수보강 정량화 이력 모델)

  • Park, Seung-Hyun;Park, Kyung Hoon;Kim, Hee Joong;Kong, Jung-Sik
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.28 no.6A
    • /
    • pp.765-778
    • /
    • 2008
  • Performance Profiles are essential to predict the performance variation over time for the bridge management system (BMS) based on risk management. In general, condition profiles based on experts opinion and/or visual inspection records have been used widely because obtaining profiles based on real performance is not easy. However, those condition profiles usually don't give a good consistency to the safety of bridges, causing practical problems for the effective bridge management. The accuracy of performance evaluation is directly related to the accuracy of BMS. The reliability of the evaluation is important to produce the optimal solution for distributing maintenance budget reasonably. However, conventional methods of bridge assessment are not suitable for a more sophisticated decision making procedure. In this study, a method to compute quantitative performance profiles has been proposed to overcome the limitations of those conventional models. In Bridge Management Systems, the main role of performance profiles is to compute and predict the performance of bridges subject to lifetime activities with uncertainty. Therefore, the computation time for obtaining an optimal maintenance scenario is closely related to the efficiency of the performance profile. In this study, the Response Surface Method (RSM) based on independent and important design variables is developed for the rapid computation. Steel box bridges have been investigated because the number of independent design variables can be reduced significantly due to the high dependency between design variables.

A Study on the capacity degradation impact analysis and simulation based on battery aging model for hybrid vehicles (하이브리드 자동차용 배터리 열화 모델 기반 용량 감소 영향성 분석 및 시뮬레이션 기반 연구)

  • Kim, Jaewon;Park, Jinhyeong;Kim, Jaeyeong;Yoo, Sungil;Kim, Jonghoon
    • Proceedings of the KIPE Conference
    • /
    • 2020.08a
    • /
    • pp.377-378
    • /
    • 2020
  • 본 논문에서는 열화에 따른 하이브리드 차량의 연비 특성을 분석하기 위해 시뮬레이션을 통한 연구를 진행하였다. 전기적 특성 실험 기반으로 배터리 내부 파라미터가 열화에 어떤 영향을 미치는지 분석을 하고 이를 기반으로 하이브리드 차량모델을 통해 시뮬레이션을 진행하였다. 분석 결과를 통해 배터리 열화 상태에 따른 State-Of-Charge (SOC) 및 연비효율 그래프의 변화 추이를 비교하였다.

  • PDF

Development of a numerical modelling technique for evaluation of a long-term chemical deterioration of tunnel shotcrete lining (터널 숏크리트 라이닝의 장기 화학적 열화 손상 평가를 위한 수치 모델링 기법 개발)

  • Shin, Hyu-Soung;Kim, Dong-Gyou
    • Journal of Korean Tunnelling and Underground Space Association
    • /
    • v.9 no.3
    • /
    • pp.299-307
    • /
    • 2007
  • In this study, a new concept for simulating a physical damage of tunnel shotcrete lining due to a long-term chemical deterioration has been proposed. It is known that the damage takes place mainly by internal cracks, reduction of stiffness and strength, which results mainly from volume expansion of the lining and corrosion of cement materials, respectively. This damage mechanism of shotcrete lining appears similar in most kinds of chemical reactions in tunnels. Therefore, the mechanical deterioration mechanism induced by a series of chemical reactions was generalized in this study and mathematically formulated in the framework of thermodynamics. The numerical model was implemented to a 3D finite element code, which can be used to simulate behaviour of tunnel structures undergoing external loads as well as chemical deterioration in time. A number of illustrative examples were given to show a feasibility of the model in tunnel designs.

  • PDF

On Diagnosis Measurement under Dynamic Loading of Ball Bearing using Numerical Thermal Analysis and Infrared Thermography (전산 열해석 및 적외선 열화상을 이용한 볼베어링의 동적 하중에 따른 진단 계측에 관한 연구)

  • Hong, Dong-Pyo;Kim, Ho-Jong;Kim, Won-Tae
    • Journal of the Korean Society for Nondestructive Testing
    • /
    • v.33 no.4
    • /
    • pp.355-360
    • /
    • 2013
  • With the modern machinery towards the direction of high-speed development, the thermal issues of mechanical transmission system and its components is increasingly important. Ball bearing is one of the main parts in rotating machinery system, and is a more easily damaged part. In this paper, bearing thermal fault detection is investigated in details Using infrared thermal imaging technology to the operation state of the ball bearing, a preliminary thermal analysis, and the use of numerical simulation technology by finite element method(FEM) under thermal conditions of the bearing temperature field analysis, initially identified through these two technical analysis, bearing a temperature distribution in the normal state and failure state. It also shows the reliability of the infrared thermal imaging technology. with valuable suggestions for the future bearing fault detection.

Proposal of Domestic Road Bridge Deck Deterioration Models and Forecast of Replacement Demand (국내 도로교량 바닥판 열화모델 제안 및 교체 수요 예측)

  • Kim, Jin-Kwang;Jang, Il-Young
    • Journal of the Korea institute for structural maintenance and inspection
    • /
    • v.21 no.4
    • /
    • pp.61-68
    • /
    • 2017
  • Bridge decks are members that rapidly deteriorated due to various environmental factors such as heavy vehicle and deicing salt, etc. As the lifespan of bridges built in Korea increases, it is expected that the demand for replacing the deteriorated bridge decks will increase. In other countries, Accelerated Bridge Construction technology using precast decks is already actively being used as a countermeasure for replacement demand of deteriorated bridge decks. In this study, bridge decks deterioration models are proposed by collecting and analysing the condition index data of domestic bridge decks. Also, the future replacement demands of deteriorated bridge decks in terms of replacement time and replacement scale are predicted.

Building battery deterioration prediction model using real field data (머신러닝 기법을 이용한 납축전지 열화 예측 모델 개발)

  • Choi, Keunho;Kim, Gunwoo
    • Journal of Intelligence and Information Systems
    • /
    • v.24 no.2
    • /
    • pp.243-264
    • /
    • 2018
  • Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

Development of Deep Learning Based Deterioration Prediction Model for the Maintenance Planning of Highway Pavement (도로포장의 유지관리 계획 수립을 위한 딥러닝 기반 열화 예측 모델 개발)

  • Lee, Yongjun;Sun, Jongwan;Lee, Minjae
    • Korean Journal of Construction Engineering and Management
    • /
    • v.20 no.6
    • /
    • pp.34-43
    • /
    • 2019
  • The maintenance cost for road pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance preventive maintenance requires the establishment of a strategic plan through accurate prediction of road pavement. Hence, In this study, the deep neural network(DNN) and the recurrent neural network(RNN) were used in order to develop the expressway pavement damage prediction model. A superior model among these two network models was then suggested by comparing and analyzing their performance. In order to solve the RNN's vanishing gradient problem, the LSTM (Long short-term memory) circuits which are a more complicated form of the RNN structure were used. The learning result showed that the RMSE value of the RNN-LSTM model was 0.102 which was lower than the RMSE value of the DNN model, indicating that the performance of the RNN-LSTM model was superior. In addition, high accuracy of the RNN-LSTM model was verified through the comparison between the estimated average road pavement condition and the actually measured road pavement condition of the target section over time.

Finite Element Analysis of RC Structures considering Bond Characteristics (부착특성을 고려한 RC구조물의 유한요소 해석)

  • 한상호
    • Magazine of the Korea Concrete Institute
    • /
    • v.9 no.5
    • /
    • pp.157-164
    • /
    • 1997
  • 일반적으로 콘크리트와 철근간의 경계면을 나타내는 유한요소법에는 균열의 부근에서 발생하는 부착열화 현상을 고려하지 않고 있다. 이것은 균열 부근에서 과도한 부착을 초래하고 , 국소 변형과 균열의 진전에도 영향을 준다. 본 연구에서는 철근콘크리트 구조물의 균열부근에서 일어나는 부착거동의 변화를 고려한 비선형 부착응력-미끄럼 모델을 제안하였다. 철근과 콘크리트간의 경계면에는 링크요소를 이용하였고, 링크의 특성은 철근을 가로지르는 균열의 상태에 따라 변하도록 조정하였다. 균열의 형성상태를 정량화하고, 부착거동을 두 포락선 1) 균열로부터 충분히 떨어진 위치에서의 부착상태를 모델링한 외연포락선, 2)횡균열면에 있어서의 부착상태를 모델링한 내연포락선의 사이에 변이시키기 위하여 비국소적 손상도 개념을 도입하였다. 이 방법의 유효성을 알아보기 위하여 편재하중을 받는 T형 교각의 실험 및 해석결과를 제시하였다. 제안된 모델의 결과를 실험결과와 비교하여 본 모델의 유용성을 검증하였다.