• Journal of the Korea Institute of Information and Communication Engineering
• /
• 제27권1호
• /
• pp.15-26
• /
• 2023

The purpose of this study is to determine the artificial intelligence-based degradation index from the image of the cross-section of the microstructure taken with a scanning electron microscope of the specimen obtained by the creep test of DA-5161 SX, a nickel-based superalloy used as a material for high-temperature parts. It proposes a new method of quantification and proposes a model that predicts degradation based on Bayesian inference without destroying components of high-temperature parts of operating equipment and a creep life prediction model that predicts Larson-Miller Parameter (LMP). It is proposed that the new degradation indexing method that infers a consistent representative value from a small amount of images based on the geometrical characteristics of the gamma prime phase, a nickel-base superalloy microstructure, and the prediction method of degradation index and LMP with information on the environmental conditions of the material without destroying high-temperature parts.

• Journal of the Korean Society for Railway
• /
• 제16권6호
• /
• pp.466-472
• /
• 2013

The use of a concrete track is gradually growing in urban and high-speed railways in many part of the world. The resilient pad, which is essentially when concrete tracks are used, plays the important role of relieving the impact caused by train loads. The simple fatigue test[1] to estimate the variable stiffness of resilient pads is usually performed, but it differs depending on the practical conditions of different railways. In this study, the static stiffness levels of used resilient pads according to passing tonnages levels were measured in laboratory tests. Also, the simple fatigue test and the multi-stress accelerated degradation test for new resilient pads were performed in a laboratory. The static stiffness of the used pad was compared with the results of tests of usage times and cycles. The results of the comparison showed that the variable static stiffness levels of the used pad were similar to results of the multi-stress accelerated degradation test considering the fatigue and heat load. With a T-NT equation related to the degree of the multi-stress accelerated degradation, a model of multi-stress accelerated degradation for a resilient pad was devised. It was found through this effort that the total acceleration factor was approximately 2.62. Finally, this study proposes an equation for a multi-stress accelerated degradation model for polyurethane resilient pads.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• 제41권8호
• /
• pp.1-8
• /
• 2004

Experimental results are presented for gate oxide degradation, such as SILC and soft breakdown, and its effect on device parameters under negative and positive bias stress conditions using n-MOSFET's with 3 nm gate oxide. The degradation mechanisms are highly dependent on stress conditions. For negative gate voltage, both interface and oxide bulk traps are found to dominate the reliability of gate oxide. However, for positive gate voltage, the degradation becomes dominated mainly by interface trap. It was also found the trap generation in the gate oxide film is related to the breakage of Si-H bonds through the deuterium anneal and additional hydrogen anneal experiments. Statistical parameter variations as well as the “OFF” leakage current depend on both electron- and hole-trapping. Our results therefore show that Si or O bond breakage by tunneling electron and hole can be another origin of the investigated gate oxide degradation. This plausible physical explanation is based on both Anode-Hole Injection and Hydrogen-Released model.

• Journal of the Korean Society of Propulsion Engineers
• /
• 제23권4호
• /
• pp.42-49
• /
• 2019

This paper presents a method to predict the storage reliability of springs for turbo engine components based on an accelerated degradation test. The reliability assessment procedure for springs is established to proceed with the accelerated degradation test. The spring constant is selected as the performance degradation characteristic, the temperature is determined to be the stress factor that deteriorates the spring constant. The storage tests are performed at three temperature test conditions. The spring constant is measured periodically to check the degradation status of the springs. Failure times of the springs are predicted by using the degradation model. Finally, the storage lifetime of the springs at normal use conditions is predicted using an accelerated model and failure times of all test conditions.

• Journal of Intelligence and Information Systems
• /
• 제24권2호
• /
• 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.

• Korean Journal of Construction Engineering and Management
• /
• 제20권6호
• /
• 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.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
• /
• 한국윤활학회 1991년도 제14회 학술강연회초록집
• /
• pp.8-13
• /
• 1991

엔진유는 엔진내에서 사용됨에 다라 마모방지제의 소모, 브로바이 가스의 혼입, 열화생성물과 첨가제간의 반응등의 영향을 받아 서서히 열화되기 시작하며, 아울러 마모방지성능 또한 변화되어간다. 열화생성물 중의 어떤 극성산화물이나 고분자생성물은 엔진마모의 감소에 기여하나, 일부 산성생성물은 부식마모를 일으킬 수도 있으며, 엔진내에서 발생되는 마모분중에는 어브레시브 마모를 발생시키는 것도 있다. 또한, 브로바이 생성물중에는 마찰면을 직접 부식시키는 성분도 있으며, 그외 부식성이 약한 브로바이 성분들도 첨가제와의 반응을 통하여 간접적으로 엔진유의 마모방지성능에 영향을 미친다. 필자는 최근의 연구에서 엔진유의 마모방지성능은 엔진에서의 열화정도에 달 현격히 변화하며, 또한 사용유의 전산가증가치와 마모량간에는 명확한 상관관계가 있다는 것을 보고한 바 있다. 본보고에서도 사용유에 함유되어 있는 성분중 마모방지성능에 크게 영향을 미치는 하이드로퍼옥사이드를 선택하여, 그 함유유인 모델열화유로 윤활하는 마모시험을 수행하여 얻은 결과에 관하여 검토하고자 한다.

• Journal of the Korea Computer Graphics Society
• /
• 제25권3호
• /
• pp.1-9
• /
• 2019

The image obtained from systems such as autonomous driving cars or fire-fighting robots often suffer from several degradation such as noise, motion blur, and compression artifact due to multiple factor. It is difficult to apply image recognition to these degraded images, then the image restoration is essential. However, these systems cannot recognize what kind of degradation and thus there are difficulty restoring the images. In this paper, we propose the deep neural network, which restore natural images from images degraded in several ways such as noise, blur and JPEG compression in situations where the distortion applied to images is not recognized. We adopt the channel attention modules and skip connections in the proposed method, which makes the network focus on valuable information to image restoration. The proposed method is simpler to train than other methods, and experimental results show that the proposed method outperforms existing state-of-the-art methods.

• Proceedings of the Korea Concrete Institute Conference
• /
• 한국콘크리트학회 2009년도 춘계 학술대회 제21권1호
• /
• pp.259-260
• /
• 2009

Many concrete structures have suffered from carbonation or chloride ion diffusion induced reinforcement corrosion, and a number of studies have been done on these topics. Many studies were mostly confined to the single deterioration of carbonation or chloride ion, although the environment actually presents a combined condition. This paper tried to develop the approach to compute re-diffusion of de-sorbed chloride due to carbonation of concrete. This is a key for successful combined deterioration model of carbonation and chloride. It is thought that this paper can contribute to express mathematically chloride enrichment and re-diffusion of chloride at front of carbonation.

• Proceedings of the Korean Reliability Society Conference
• /
• 한국신뢰성학회 2004년도 정기학술대회
• /
• pp.239-246
• /
• 2004

Accelerated degradation test (ADT) can be a useful tool for assessing the reliability when few or even no failure are expected in an accelerated life test. In this paper, MLCC (Multilayer Ceramic Capacitors), a sort of passive components which have large capacitance(X7R -55$^{\circ}C$~1$25^{\circ}C$) have been tested, and least-square analyses are used to illustrate our approach in which amount of degradation of a DUT following log-normal distribution. We assumed a simple and useful linear model to describe the amount of degradation over time subjected to different voltage levels applied. Tests for linearity of the performance-time relationship, and provide tests for how well the assumptions hold. Also, by using Eyring Model, MLCC's mean life time is assessed.