• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.610-614
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• 1996

As the run out error and misalignment of ball screw connected directly to guide table largely affect the motion accuracy of guideway, floating coupling that releases the table from screw nut except feed and rotational direction is needed todecrease its influences. The purpose of this study is to propose a practical model floating coupling of ball serew for high precision feeding system. The straightness, dynanic characteristics and micro step response of hydrostatic guideway, mounted with three types of coupling fixed type, leaf spring type and hydrostatic type, are tested and compared. From the resuts of experiments, it is proved that a hydrostatic type floating coupling is superior to other couplings and is available to high precision feeding system with ball screw.

• 문화기술의 융합
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• 제10권3호
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• pp.801-807
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• 2024

선형 로봇은 자동화 시스템에서 부품의 이송이나 위치 결정에 널리 사용되며 보통 높은 정밀도가 요구된다. 선형 로봇을 응용한 시스템의 제작회사에서는 로봇의 이상 유무를 작업자가 판단하는데, 작업자의 숙련도에 따라 이상 상태를 판단하는 정확도가 달라진다. 최근에는 인공지능 등의 기술을 사용하여 로봇 스스로 이상을 검출하는 방법에 관한 연구가 진행되고 있다. 본 논문에서는 전이 학습을 이용하여 선형 로봇의 볼 스크류 정렬 이상과 선형 레일 정렬 이상을 검출하는 시스템을 제안하고 가속도 센서와 토크 센서 정보를 이용한 별개의 실험을 통해 제안한 시스템의 이상 검출 성능을 검증 및 비교한다. 센서로부터 얻어진 신호를 스펙트로그램 이미지로 변환한 후, 영상 인식 인공지능 분류기를 사용하여 이상의 종류를 진단하였다. 제안한 방법은 선형 로봇뿐만 아니라 일반적인 산업용 로봇에도 적용할 수 있을 것으로 기대한다.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1998년도 제28회 추계학술대회
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• pp.343-349
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• 1998

A modeling of machined geometry and cutting force was proposed for the case of round shape machining, and the effects of internally machined profile are analyzed and its realiability was verified by the experiments of roundness tester, especially in boring operation in lathe. Also, harmonic cutting force model was proposed with the parameter of specific cutting force, chip width and chip thickness, and in this study, we can see that bored workpiece profile was also mapped into cutting force signal with this model. In general, we can calculated the theoretical lobe profile with arbitrary multilobe. But in real experiments, the most frequently measured numbers are 3 and 5 lobe profile in experiments. With this results, we can predict that these results may be applied to round shape machining such as drilling, boring, ball screw and internal grinding operation with the same method.

• International Journal of Internet, Broadcasting and Communication
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• 제16권3호
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• pp.121-138
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• 2024

Artificial intelligence is crucial to manufacturing productivity. Understanding the difficulties in producing disruptions, especially in linear feed robot systems, is essential for efficient operations. These mechanical tools, essential for linear movements within systems, are prone to damage and degradation, especially in the LM guide, due to repetitive motions. We examine how explainable artificial intelligence (XAI) may diagnose wafer linear robot linear rail clearance and ball screw clearance anomalies. XAI helps diagnose problems and explain anomalies, enriching management and operational strategies. By interpreting the reasons for anomaly detection through visualizations such as Class Activation Maps (CAMs) using technologies like Grad-CAM, FG-CAM, and FFT-CAM, and comparing 1D-CNN with 2D-CNN, we illustrates the potential of XAI in enhancing diagnostic accuracy. The use of datasets from accelerometer and torque sensors in our experiments validates the high accuracy of the proposed method in binary and ternary classifications. This study exemplifies how XAI can elucidate deep learning models trained on industrial signals, offering a practical approach to understanding and applying AI in maintaining the integrity of critical components such as LM guides in linear feed robots.