• International Journal of Internet, Broadcasting and Communication
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• 제15권4호
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• pp.270-278
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• 2023

We propose a container orchestration system for process workloads that combines the potential of big data and machine learning technologies to integrate enterprise process-centric workloads. This proposed system analyzes big data generated from industrial automation to identify hidden patterns and build a machine learning prediction model. For each machine learning case, training data is loaded into a data store and preprocessed for model training. In the next step, you can use the training data to select and apply an appropriate model. Then evaluate the model using the following test data: This step is called model construction and can be performed in a deployment framework. Additionally, a visual hierarchy is constructed to display prediction results and facilitate big data analysis. In order to implement parallel computing of PCA in the proposed system, several virtual systems were implemented to build the cluster required for the big data cluster. The implementation for evaluation and analysis built the necessary clusters by creating multiple virtual machines in a big data cluster to implement parallel computation of PCA. The proposed system is modeled as layers of individual components that can be connected together. The advantage of a system is that components can be added, replaced, or reused without affecting the rest of the system.

• 한국항행학회논문지
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• 제23권5호
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• pp.361-366
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• 2019

항공전자시스템을 개발하는 과정에서 개별 구성품의 기능 및 연동 검증을 위한 통합시험환경(SIL; system integration laboratory)을 구성한다. 이러한 SIL의 구성품 개별 검증 및 시스템 통합 시 각 탑재장비의 기능 및 연동을 모의하는 SIL 모델을 개발하여 이용한다. SIL 모델은 실 장비와 연동되기 전 연동통제문서(ICD; interface control document)에 정의된 모든 데이터에 대해 선 검증되어야하며 ICD 변경 혹은 기능 변경 발생 시에도 재 검증되어야한다. 하지만 SIL모델의 검증의 수동 수행 시 개별 SIL모델의 검증에도 상당한 시간이 소요된다. 이러한 시간상의 문제로 ICD 변경이나 일부 기능 변경 시에는 SIL 모델의 영향성을 판단하여 선택적 회귀시험이 이루어지곤 한다. 본 논문에서는 이러한 SIL 모델의 검증에 소요되는 시간을 최소화하여 회귀시험 수행 시 모든 시험항목의 검증이 가능하도록 SIL 모델 검증 자동화 방안을 설계하고 설계에 따른 SIL 모델 검증 자동화도구를 개발하여 SIL 모델 검증자동화 설계의 유용성을 검증하였다.

• 한국산학기술학회논문지
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• 제16권12호
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• pp.8753-8759
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• 2015

터빈 발전 사이클에서의 안정적인 발전 출력 유지관리를 위해서는 검증된 성능 측정 데이터 그룹과 이를 바탕으로 한 발전 출력 성능 계산 절차의 수립이 필요하다. ASME PTC(Performance Test Code)의 성능 계산 절차를 기반으로 본 연구에서는 터빈 출력에 의한 발전기 출력 성능 산정을 위해서 터빈 팽창선 모델과 발전기 출력 측정 데이터의 입력 검증 모델을 구성하였다. 또한 불확실한 측정 데이터에 대한 검증 모델도 구성하였다. 지난 연구에서는 신경회로망과 커널 회귀의 학습 방법을 사용하였으나 본 연구에서는 미측정 데이터에 대한 보완을 하기 위하여 서포트 벡터 머신 모델을 사용하여 발전기 출력 계산 데이터의 학습 모델을 구성하였으며, 학습 모델 구성을 위해서 관련 변수의 선정을 위한 절차와 학습 데이터 구간을 설정하는 알고리듬을 개발하였다. 학습의 결과 오차는 약 1% 범위 안에 있게 되어 추정 및 학습 모델로서 유용함을 입증하였다. 이 학습 모델을 사용하여 측정 데이터 중 상실된 부분에 대한 추정 모델을 구성함으로써, 터빈 사이클 보정 성능 계산의 신뢰성을 향상시킬 수 있음을 검증하였다.

• Transactions on Control, Automation and Systems Engineering
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• 제2권1호
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• pp.40-46
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• 2000

In this paper, a transient identification based on a Hidden Markov Model (HMM) has been suggested and evaluated experimentally for the classification of transients in the dynamic process. The transient can be identified by its unique time dependent patterns related to the principal variables. The HMM, a double stochastic process, can be applied to transient identification which is a spatial and temporal classification problem under a statistical pattern recognition framework. The HMM is created for each transient from a set of training data by the maximum-likelihood estimation method. The transient identification is determined by calculating which model has the highest probability for the given test data. Several experimental tests have been performed with normalization methods, clustering algorithms, and a number of states in HMM. Several experimental tests have been performed including superimposing random noise, adding systematic error, and untrained transients. The proposed real-time transient identification system has many advantages, however, there are still a lot of problems that should be solved to apply to a real dynamic process. Further efforts are being made to improve the system performance and robustness to demonstrate reliability and accuracy to the required level.

• International Journal of Control, Automation, and Systems
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• 제5권5호
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• pp.515-525
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• 2007

In this paper, we develop a co-design methodology of stochastic optimal controllers and network parameters that optimizes the overall quality of control (QoC) in networked control systems (NCSs). A new dynamic model for NCSs is provided. The relationship between the system stability and performance and the sampling frequency is investigated, and the analysis of co-design of control and network parameters is presented to determine the working range of the sampling frequency in an NCS. This optimal sampling frequency range is derived based on the system dynamics and the network characteristics such as data rate, time-delay upper bound, data-packet size, and device processing time. With the optimal sampling frequency, stochastic optimal controllers are designed to improve the overall QoC in an NCS. This co-design methodology is a useful rule of thumb to choose the network and control parameters for NCS implementation. The feasibility and effectiveness of this co-design methodology is verified experimentally by our NCS test bed, a ball magnetic-levitation (maglev) system.

• 생물환경조절학회지
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• 제1권2호
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• pp.162-168
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• 1992

As the automation of nutrient solution management proceeds in the field of hydroponics, effective supporting systems to manage the nutrient solution by computer become needed. This study was attempt to predict the EC of nutrient solution using the neural networks. The multilayer perceptron consisting of 3 layers with the back propagation learning algorithm was selected for EC prediction, of which nine variables in the input layer were the concentrations of each ion and one variable in the output layer the EC of nutrient solution. The meq unit in ion concentration was selected fir input variable in the input layer. After the 10,000 learning sweeps with 108 sample data, the comparison of predicted and measured ECs for 72 test data showed good agreements with the correlation coefficient of 0.998. In addition, the predicted ECs by neural network showed relatively equal or closer to the measured ones than those by current complicated models.

• Asia pacific journal of information systems
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• 제1권1호
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• pp.63-86
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• 1991

In this paper, our concern is the artificial neural network-based patten classification, when can resolve the difficulties in the Autoregressive Moving Average(ARMA) model identification problem To effectively classify a time series into an approriate ARMA model, we adopt the Multi-layered Backpropagation Network (MLBPN) as a pattern classifier, and Extended Sample Autocorrelation Function (ESACF) as a feature extractor. To improve the classification power of MLBPN's we suggest an integrated neural network system which consists of an AR Network and many small-sized MA Networks. The output of AR Network which will gives the MA order. A step-by-step training strategy is also suggested so that the learned MLBPN's can effectively ESACF patterns contaminated by the high level of noises. The experiment with the artificially generated test data and real world data showed the promising results. Our approach, combined with a statistical parameter estimation method, will provide a way to the automation of ARMA modeling.

• 한국측량학회지
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• 제25권6_1호
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• pp.575-583
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• 2007

Surface segmentation aims to represent the terrain as a set of bounded and analytically defined surface patches. Many previous segmentation methods have been developed to extract planar patches from LIDAR data for building extraction. However, most of them were not fully satisfactory for more general applications in terms of the degree of automation and the quality of the segmentation results. This is mainly caused from the limited information derived from LIDAR data. The purpose of this study is thus to develop an automatic method to perform surface segmentation by combining not only LIDAR data but also images. A region-based method is proposed to generate a set of planar patches by grouping LIDAR points. The grouping criteria are based on both the coordinates of the points and the corresponding intensity values computed from the images. This method has been applied to urban data and the segmentation results are compared with the reference data acquired by manual segmentation. 76% of the test area is correctly segmented. Under-segmentation is rarely founded but over-segmentation still exists. If the over-segmentation is mitigated by merging adjacent patches with similar properties as a post-process, the proposed segmentation method can be effectively utilized for a reliable intermediate process toward automatic extraction of 3D model of the real world.

• 한국항공우주학회지
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• 제49권10호
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• pp.871-877
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• 2021

항공기 결함은 항공기 운영 및 조종사의 생명과 직결된 중요한 사항으로 항공기 조종 중 발생하는 임무 소프트웨어의 결함은 조종사 임무수행 및 안전에 심각한 영향을 미친다. 항공기 개발을 주관하는 단체나 소프트웨어 결함을 개발 초기에 식별하고 제거하기 위해 프로세스를 강화하고 많은 공수와 시간을 할애하고 있지만 임무 소프트웨어의 특성상 타 항전 장비와 강한 기능적 결합도(Coupling) 및 높은 복잡도(Complexity)를 가지고 있어 기존 시험 방법을 통한 소프트웨어 결함 식별 및 제거에 제약이 따른다. 본 연구는 임무 컴퓨터 연동 장비의 통신 데이터 중 피드백 데이터의 기댓값 검증을 자동화하는 도구를 개발하여 데이터 무결성 검증을 통한 임무 소프트웨어 건전성 확보 및 시험 비용 감소 효과를 분석한다.

• 한국자동차공학회논문집
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• 제12권4호
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• pp.119-128
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• 2004

With the growing traffic density and increasing comfort requirements, the automation of the drive train will gain importance in vehicles. The automatic clutch actuation relieves the drivers especially in urban driving and stop-and-go traffic conditions. This paper describes the dynamic modeling of a clutch actuator and clutch spring. The dynamic model of the clutch system is developed using MATLAB/Simulink, and evaluated by experimental data using a test rig. This performance simulator is useful to develop the clutch-by-wire (CBW) system for an automated manual transmission (AMT). The electro-mechanical type CBW system is also implemented as an automatic clutch for AMT. The prototype of CBW system is designed and implemented systematically, which is composed of an electric motor, worm gear and slider-crank mechanism. The test rig is developed to perform the basic function test of the automatic clutch, and the developed prototype is validated by the experimental data on the test rig.