• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.56-64
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• 2018

In recent years, imbalanced data is one of the most important and frequent issue for quality control in industrial field. As an example, defect rate has been drastically reduced thanks to highly developed technology and quality management, so that only few defective data can be obtained from production process. Therefore, quality classification should be performed under the condition that one class (defective dataset) is even smaller than the other class (good dataset). However, traditional multi-class classification methods are not appropriate to deal with such an imbalanced dataset, since they classify data from the difference between one class and the others that can hardly be found in imbalanced datasets. Thus, one-class classification that thoroughly learns patterns of target class is more suitable for imbalanced dataset since it only focuses on data in a target class. So far, several one-class classification methods such as one-class support vector machine, neural network and decision tree there have been suggested. One-class support vector machine and neural network can guarantee good classification rate, and decision tree can provide a set of rules that can be clearly interpreted. However, the classifiers obtained from the former two methods consist of complex mathematical functions and cannot be easily understood by users. In case of decision tree, the criterion for rule generation is ambiguous. Therefore, as an alternative, a new one-class classifier using hyper-rectangles was proposed, which performs precise classification compared to other methods and generates rules clearly understood by users as well. In this paper, we suggest an approach for improving the limitations of those previous one-class classification algorithms. Specifically, the suggested approach produces more improved one-class classifier using hyper-rectangles generated by using Gaussian function. The performance of the suggested algorithm is verified by a numerical experiment, which uses several datasets in UCI machine learning repository.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.5
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• pp.431-439
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• 2015

One of common challenges in designing modern production machines is realizing high speed motion without sacrificing accuracy. To address this challenge it is necessary to maximize the stiffness of the mechanical structure and the control system with consideration on the main disturbance input, cutting forces. This paper presents analysis technologies for realizing high stiffness in production machines. First, CAE analysis techniques to evaluate the dynamic stiffness of a machine structure and a new method to construct the physical machine model for servo controller simulations are demonstrated. Second, cutting forces generated in milling processes are analyzed to evaluate their effects on the mechatronics system. In the effort to investigate the interaction among the structure, controller, and process, a flexible multi-body dynamics simulation method is implemented on a magnetic bearing stage as an example. The presented technologies can provide better understandings on the mechatronics system and help realizing high stiffness production machines.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.725-732
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• 2020

This paper uses variables following as : to follow me well(0-9), it takes a lot of time to make a decision (0-9), lethargy(0-9) during physical activity in the exercise learning program of the children in the marginalized class. This paper classifies 'gender', 'physical education classroom', and 'upper, middle and lower' of age, and observe changes in ego-resiliency and self-control through sports rehabilitation therapy to find out changes in mental health. To achieve this, the data acquired was merged and the characteristics of large and small numbers were removed using the Label encoder and One-hot encoding. Then, to evaluate the performance by applying each algorithm of MLP, SVM, Dicesion tree, RNN, and LSTM, the train and test data were divided by 75% and 25%, and then the algorithm was learned with train data and the accuracy of the algorithm was measured with the Test data. As a result of the measurement, LSTM was the most effective in sex, MLP and LSTM in physical education classroom, and SVM was the most effective in age.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.207-214
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• 2014

If two or more Permanent Magnet Synchronous Motors (PMSM) can be controlled by one inverter, a train can be driven by less energy than the present Induction Motor (IM) drive system. First, this paper proposes a method for simulating the movement of wheels and a vehicle to develop a control method. Next, a method is presented for controlling two or more PMSMs by one inverter.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.248-253
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• 1997

The ideal surface roughness is obtained by tool geometry and feed rate in face milling. however actual surface roughness is affected by various factors such as cutting conditions. vibration and used tool. To improve the quality and productivity of the machining parts, lots of research on the evaluation of tool life and control of surface roughness has been required. Therefore, the width of flank wear, cutting force, and surface roughness are monitored to analyse the characteristics of surface roughness. This experimental investigation is mainly focused on the characteristics of surface roughness in multi-insert milling using TiN coated tool.

• The Journal of the Acoustical Society of Korea
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• v.10 no.6
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• pp.23-42
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• 1991

본 논문은 시스템 운동학적 자유보다도 많은 수의 input을 사용하여 비선형 구속조건을 갖는 메 카니즘의 정역학적 평형을 유지시키는 경우와 같이 일반 로봇 시스템의 협력 작업시 일어나는 antagonistic stiffness를 연구하였다. 이러한 antagonistic 상황은 coordinations of multiple manipulators, multi-fingered end-efector, walking machine, 그리고 인간의 움직임등을 포함하는 많은 로봇 시스템의 작동시에 일어난다. Antagonism으로 야기되는 stiffness는 이러한 시스템의 특성을 파악하는 좋은 척도 가 될 수 있다. Antagonistic stiffness의 개념은 시스템을 구성하는 강체들의 상대 변위의 함수로 얻어 지기 때문에 바강체들이 변형하는 특성을 나타내는 structural stiffness와는 구별된다. 따라서 이 개념은 여유입력들에 의해 얻어지는 시스템의 effective stiffness로 해석될 수 있고, 일반 로봇 mechanism의 개 경로 안정도의 척도로 이용될 수 있으며 목적에 따라서 stiffness의 제어가 가능한 비선형 spring을 만 드는 데에도 응용이 가능하다. 본 논문에서는 antagonism이 일어나는 몇가지 상황에서의 stiffness 특성 과 개경로 안정성 조건등을 해석적, 기하학적 관점에서 다루었다.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.615-617
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• 1999

In this paper, we present a decentralized robust adaptive fuzzy controller for the transient stability and voltage regulation of a multimachine power system under a sudden fault. Power systems have uncertain dynamics due to various effects such as lightning, severe storms and equipment failure in addition to interconnections between generators. Hence a robust controller to deal with these uncertainties is needed. Simulation results show that satisfactory performance is achieved by the proposed controller.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.31-40
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• 1993

This paper deals with the modeling and scheduling for FMC(Flexible Manufacturing Cells). The FMC system composed of unit or multi cells is capable of improving productivity with flexibility for machine. However, the properties of multiple jobs and various alternatives results in tne dynamic states which make system management very complex. The extended Peti nets are used to represent for complex properties of FMC which performs short-term scheduling and dynamic operational scheduling. The hierarchical control structure and integlligent scheduling through expert module are adopted for efficiency of FMC operations. The computer simulation reveals that intelligent scheduling method is better than heuristics in various performance indices.

• International Journal of Precision Engineering and Manufacturing
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• v.9 no.1
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• pp.34-38
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• 2008

The surface texture of a product is generally produced by etching or sandblasting. However, these techniques have problems related to repeatability and environmental pollution. Since current milling machines can produce small parts at the micrometer or nanometer level, the resolution of milling exceeds the manufactured dimensions of the surface texture produced by etching or sand-blasting. A method for generating surface texture by milling is proposed and demonstrated. The proposed method was demonstrated by actual milling using a three- or five-axis control machine, and the machined surface texture was measured with an interferometer to allow comparison with the designed shape. The measurement results demonstrate that the proposed method can generate a wide-area surface texture with good machining repeatability.