• 한국지능시스템학회논문지
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• 제18권5호
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• pp.718-723
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• 2008

베어링은 각종 설비에서 활용되는 중요한 기계요소 중 하나이다. 설비고장의 상당수는 베어링의 결함이나 파손에 기인하고 있다. 따라서 베어링에 대한 온라인모니터링기술은 설비의 정지를 예방하고 손실을 줄이는 데 필수적이다. 본 논문은 진동 신호를 이용하여 베어링의 상태를 예측하기 위한 온라인모니터링에 대해 연구한다. 프로파일로 주어지는 진동신호는 이산 웨이블릿 변환을 통해 분석되고, 분해수준별 웨이블릿 계수로부터 얻은 통계적 특징 중 유의한 것을 선별하고자 분산분석 (ANOVA)을 이용한다. 선별된 특징벡터는 Support Vector Machine (SVM)의 입력이 되는 데, 본 논문에서는 다중클래스 분류문제를 다루기 위한 계층적 SVM 트리를 제안한다. 수치실험 결과, 제안된 방법은 베어링의 결함을 분류하는 데 우수한 성능을 갖는 것으로 나타났다.

• 한국ITS학회 논문지
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• 제21권3호
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• pp.42-52
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• 2022

BIS(Bus Information System) 서비스는 대도시를 포함하여 중소도시까지 전국적으로 확대운영되는 추세이며, 이용자의 만족도는 지속적으로 향상되고 있다. 이와 함께 버스도착시간 신뢰성 향상 관련 기술개발, 오차 최소화를 위한 개선 연구가 지속되고 있으며 무엇보다 정보 정확도의 중요성이 부각되고 있다. 본 연구에서는 기계학습 방법인 LSTM을 이용하여 정확도 성능을 평가하였으며 기존 칼만필터, 뉴럴 네트워크 등 방법론과 비교하였다. 실제 여행시간과 예측값에 대해 표준오차를 분석한 결과 LSTM 기계학습 방법이 기존 알고리즘에 비해 정확도는 약 1% 높고, 표준오차는 약 10초 낮은 것으로 분석되었다. 반면 총 162개 구간 중 109개 구간(67.3%) 우수한 것으로 분석되어 LSTM 방법이 전적으로 우수한 것은 아닌 것으로 나타났다. 구간 특성 분석을 통한 알고리즘 융합시 더욱 향상된 정확도 예측이 가능할 것으로 판단된다.

• Geomechanics and Engineering
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• 제20권4호
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• pp.345-358
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• 2020

Numerous studies have repeatedly demonstrated the efficiency of using skirts to increase the bearing capacity and to reduce settlement of shallow foundations subjected to static loads. However, no efforts have been made to study the efficiency of using these skirts to reduce settlement produced by machine vibration, although machines are very sensitive to settlement and the foundations of these machines should be designed properly to ensure that the settlement produced due to machine vibration is very small. This research has been conducted to investigate the efficiency of using skirts as a technique to reduce the settlement of a strip foundation subjected to machine vibration. A two-dimensional finite element model has been developed, validated, and employed to achieve the aim of the study. The results of the analyses showed that the use of skirts reduces the settlement produced due to machine vibration. However, the percentage decrease of the settlement is remarkably influenced by the density of the soil and the frequency of vibration, where it rises as the frequency of vibration increases and declines as the soil density rises. It was also found that increasing skirt length increases the percentage decrease of the settlement. Importantly, the results obtained from the analyses have been utilized to derive new dynamic impedance values that implicitly consider the presence of skirts. Finally, novel design equations of dynamic impedance that implicitly account to the effect of the skirts have been derived and validated utilizing a new intelligent data driven method. These new equations can be used in future designs of skirted strip foundations subjected to machine vibration.

• 한국전자통신학회논문지
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• 제11권10호
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• pp.989-994
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• 2016

본 연구는 논에 적용된 수위센서, 송수구 그리고 배수구 장치를 통하여 수위 관리를 수행 한다. 게이트웨이는 LoRa 접속을 통하여 수위센서 물높이 정보를 IoT(: Internet of Thing) 플랫폼에 oneM2M(: Machine to Machine) 규격으로 정보전달 한다. IoT 플랫폼에서 요청하는 물의 높이에 따라서, 게이트웨이는 송수구 또는 배수구 모터 스위치를 On 또는 Off하고 수위센서 정보를 전달한다. IoT 플랫폼은 물높이의 조건에 따라 지능적인 어플리케이션 기능을 수행한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4308-4325
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• 2021

The importance and necessity of artificial intelligence, particularly machine learning, has recently been emphasized. In fact, artificial intelligence, such as intelligent surveillance cameras and other security systems, is used to solve various problems or provide convenience, providing solutions to problems that humans traditionally had to manually deal with one at a time. Among them, information security is one of the domains where the use of artificial intelligence is especially needed because the frequency of occurrence and processing capacity of dangerous codes exceeds the capabilities of humans. Therefore, this study intends to examine the definition of artificial intelligence and machine learning, its execution method, process, learning algorithm, and cases of utilization in various domains, particularly the cases and contents of artificial intelligence technology used in the field of information security. Based on this, this study proposes a method to apply machine learning technology to the method of classifying and detecting malware that has rapidly increased in recent years. The proposed methodology converts software programs containing malicious codes into images and creates training data suitable for machine learning by preparing data and augmenting the dataset. The model trained using the images created in this manner is expected to be effective in classifying and detecting malware.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.144-146
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• 2021

Idiopathic pulmonary fibrosis (IPF) is one of the most dreadful lung diseases which effects the performance of the lung unpredictably. There is no any authentic natural history discovered yet pertaining to this disease and it has been very difficult for the physicians to diagnosis this disease. With the advent of Artificial intelligent and its related technologies this task has become a little bit easier. The aim of this paper is to develop and to explore the machine learning models for the prediction and diagnosis of this mysterious disease. For our study, we got IPF dataset from Haeundae Paik hospital consisting of 2425 patients. This dataset consists of 502 features. We applied different data preprocessing techniques for data cleaning while making the data fit for the machine learning implementation. After the preprocessing of the data, 18 features were selected for the experiment. In our experiment, we used different machine learning classifiers i.e., Multilayer perceptron (MLP), Support vector machine (SVM), and Random forest (RF). we compared the performance of each classifier. The experimental results showed that MLP outperformed all other compared models with 91.24% accuracy.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1977-1978
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• 2006

This paper discusses the method of vision based sensor fusion system for biped robot walking. Most researches on biped walking robot have mostly focused on walking algorithm itself. However, developing vision systems for biped walking robot is an important and urgent issue since biped walking robots are ultimately developed not only for researches but to be utilized in real life. In the research, systems for environment recognition and tele-operation have been developed for task assignment and execution of biped robot as well as for human robot interaction (HRI) system. For carrying out certain tasks, an object tracking system using modified optical flow algorithm and obstacle recognition system using enhanced template matching and hierarchical support vector machine algorithm by wireless vision camera are implemented with sensor fusion system using other sensors installed in a biped walking robot. Also systems for robot manipulating and communication with user have been developed for robot.

• International Journal of Precision Engineering and Manufacturing
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• 제4권5호
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• pp.27-33
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• 2003

G-code, another name of ISO6983, has been a popular commanding language for operating machine tools. This G-code, however, limits the usage of today's fast evolving high-performance hardware. For intelligent machines, the communications between machine and CAD/CAM departments become important, but the loss of information during generating G-code makes the production department isolated. The new standard for operating machine tools, named STEP-NC is just about to be standardized as ISO14649. As this new standard stores CAD/CAM information as well as operation commands of CNC machines, and this characteristic makes this machine able to exchange information with other departments. In this research, the new CNC machine operated by STEP-NC was built and tested. Unlike other prototypes of STEP-NC milling machines, this system uses the STEP-NC file in XML file form as data input. This machine loads information from XML file and deals with XML file structure. It is possible for this machine to exchange information to other databases using XML. The STEP-NC milling machines in this research loads information from the XML file, makes tool paths for two5D features with information of STEP-NC, and machines automatically without making G-code. All software is programmed with Visual $C^{++}$, and the milling machine is built with table milling machine, step motors, and motion control board for PC that can be directly controlled by Visual $C^{++}$ commands. All software and hardware modules are independent from each other; it allows convenient substitution and expansion of the milling machine. Example 1 in ISO14649-11 having the full geometry and machining information and example 2 having only the geometry and tool information were used to test the automatic machining capability of this system.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.828-835
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• 2008

We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2002년도 proceedings of the second asia international conference on tribology
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• pp.455-456
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• 2002

Wear is one of the main factors causing breakdown and fault of machine, so ferrography technique analyzing wear particles can be an effective way for condition monitoring and fault diagnosis. On the base of the forward multilayer neural network, a nodes self-deleting neural network model is provided in this paper. This network can itself deletes the nodes to optimize its construction. On the basis of the nodes self-deleting neural network, an intelligent ferrography diagnosis expert system (IFDES) for wear particles recognition and wear diagnosis is described. This intelligent expert system can automatically slim lip knowledge by learning from samples and realize basically the entirely automatic processing from wear particles recognition to wear diagnosis.