• 한국융합학회논문지
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• 제11권9호
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• pp.297-303
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• 2020

본 연구의 목적은 청소년기에서 성인기에 해당하는 암컷 생쥐를 대상으로 유산소 운동과 유산균 섭취가 운동 학습능력과 체중에 미치는 영향을 파악하는 것이다. 실험대상을 비운동, 중강도, 고강도 운동과 유산균 섭취, 비섭취 변인의 6집단으로 나누고 4주간 운동강도별 트레드밀과 유산균으로 처치하였다. 처치 전 후로 버티컬그리드 테스트를 수행하여 운동학습능력과 체중을 평가하였다. 버티컬그리드 테스트에서는 유산균을 섭취하고, 고강도 운동을 수행한 집단의 상행·회전·하행 속도가 가장 빨랐으며 운동을 하지 않은 비유산균집단과 유의한 차이를 보였다(p<.001). 운동을 하지 않은 비유산균집단이 가장 느린 수행 속도를 기록했다. 또한, 운동 수행과 유산균 섭취를 함께한 집단이 운동만 수행한 집단에 비해 빠른 수행 속도를 기록하는 경향을 보였다. 체중 변화를 비교한 결과 중강도 운동만 수행한 집단의 체중 증가는 운동을 수행하지 않은 비유산균집단의 체중 증가에 비해 유의하게 높았다(p=.032). 종합하면, 성장기의 유산소 운동은 운동학습 향상에 도움을 줄 수 있으며, 유산균 섭취와 병행하면 보다 효율적인 운동학습이 이루어질 수 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.778_779
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• 2009

The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. The paper is proposed maximum torque control of induction motor drive using adaptive learning neuro fuzzy controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d, q axis current $_i_{ds}$, $i_{qs}$ for maximum torque operation is derived. The proposed control algorithm is applied to induction motor drive system controlled adaptive learning neuro fuzzy controller and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the adaptive learning neuro fuzzy controller and ANN controller.

• 품질경영학회지
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• 제51권2호
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• pp.283-296
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• 2023

Purpose: The purpose of this study is to actually implement and verify whether welding defects can be detected in real time by utilizing deep learning AI solutions in the welding process of electric vehicle hairpin winding motors. Methods: AI's function and technological elements using synthetic neural network were applied to existing electric vehicle hairpin winding motor laser welding process by making special hardware for detecting electric vehicle hairpin motor laser welding defect. Results: As a result of the test applied to the welding process of the electric vehicle hairpin winding motor, it was confirmed that defects in the welding part were detected in real time. The accuracy of detection of welds was achieved at 0.99 based on mAP@95, and the accuracy of detection of defective parts was 1.18 based on FB-Score 1.5, which fell short of the target, so it will be supplemented by introducing additional lighting and camera settings and enhancement techniques in the future. Conclusion: This study is significant in that it improves the welding quality of hairpin winding motors of electric vehicles by applying domestic artificial intelligence solutions to laser welding operations of hairpin winding motors of electric vehicles. Defects of a manufacturing line can be corrected immediately through automatic welding inspection after laser welding of an electric vehicle hairpin winding motor, thus reducing waste throughput caused by welding failure in the final stage, reducing input costs and increasing product production.

• 디지털융복합연구
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• 제13권10호
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• pp.587-595
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• 2015

본 연구는 경도인지 장애 노인들을 대상으로 신체 지각에 기반한 BF 활동과 PNF 활동을 결합한 인지-운동 프로그램의 효과를 살펴봄으로서 신체 지각 기반 인지-운동 활동이 향후 치매 예방 프로그램으로 적용이 가능할지 현장 활용성을 탐색해 보고자 하였다. 검증을 위해 치매 노인들을 대상으로 2014년 5월 16일부터 2014년 8월 1일까지 12주 동안 20명을 선정하여 인지-운동 학습군(이하 CC군)과 작업 치료 학습군(이하 OT군)을 대조군으로 각각 10명으로 나누어 프로그램을 검증하였다. 연구대상자는 CC군과 OT군으로 나누어 해당 프로그램을 60분씩 12주간 참여하였으며, 인지 기능 검사(MMSE-K), 신체 균형 능력 검사(Time up & go test(이하 TUG), Tandem gait test(이하 TA)), 노인 삶의 질 검사(GQOL-D)를 실험 전(0주), 실험 후(12주)에 측정하여 비교 및 분석하였다. 연구 결과, 인지 기능 검사(MMSE-K)에서는 두 집단 모두 유사한 학습 효과를 보여주었다. 그러나, TA & GQOL-D 검사에서는 CC군이 OT 군보다 향상된 학습 효과를 보여주었다. 이러한 결과는 복합 인지-운동 학습 유형이 작업 치료 학습 유형보다 균형능력 향상과 삶의 질 향상에 기여한다는 것을 보여주는 결과로서, 향후 기억 장애 개선 프로그램으로 복합 인지 운동 활동이 고려될 수 있음을 시사한다.

• 산업경영시스템학회지
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• 제40권1호
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1999년도 전력전자학술대회 논문집
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• pp.518-521
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• 1999

This paper describes high speed squirrel cage induction motor drives without speed sensors using neural network based on Kalman filter Learning. High speed motors are receiving inverasing attentions in various applications, because of advantages of high speed, small size and light weight with same power level. Larning rate by Kalman filtering is time varying, convergence time fast, effect of initial weight between neurons is small.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1981-1986
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• 2004

In this study, the basic motor control system had been investigated. The controller for this study consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such a tracking perfect, an adaptive law based on Feedback Error Learning (FEL) is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The theory in $H^{\infty}$-Control is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.

• 조명전기설비학회논문지
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• 제19권6호
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• pp.82-86
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• 2005

PID 제어기는 산업자동화 설비에 널리 쓰이고 있다. 하지만 시스템 특성이 간헐 또는 연속적으로 변화할 때에 정밀제어를 위한 새로운 매개변수 결정이 쉽지 않다. 이를 해결하기 위한 방법으로 본 논문에서는 PID 제어기와 같은 기능을 갖는 학습이득조절기를 제안하였다. 시스템의 적절한 학습이득은 델타 학습규칙에 의해서 결정된다. 제안된 학습이득 조절기의 기능은 직류 전동기의 모의실험에 의해 확인하였다.

• 한국전자현미경학회:학술대회논문집
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• 한국현미경학회 2005년도 제36차 춘계학술대회 및 제3회 HVEM 이용자 워크샵
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• pp.116-117
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• 2005

• 기술혁신학회지
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• 제4권1호
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• pp.32-48
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• 2001

Many Korean companies have grown up through technology import, learning, development, innovation and export. This process is called as "the dynamic development process of technology". Among many companies which have grown up by way of this process, the Hyundai Motor Company has shown a very remarkable achievement in technological growth. In short, this paper deals with the growth of Korean companies in the view of the dynamic development process of technology. As a case study, the paper analyzes the Hyundai Motor Company.r Company.