인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
This article presents the latest research results on the enhancement of robot-based incremental sheet metal forming performance in detail and comprehensively. Since the low robot stiffness leads to deformations of the robot and thus deviations of the final part, the presented contributions aim for increasing the part accuracy. The article demonstrates how an advanced sensor network, analogous to a µGPS, can be established for tracking the tool pose utilizing innovative shadow imaging sensor technology. Static experiments show that a measurement uncertainty below of 50 µm is achievable after the correction of systematic errors. Additional experiments demonstrated the applicability of the sensor network for measuring the tool position on a moving robot. Based on the measurement, a robot position correction will be enabled to achieve a reduction of machine-dependent component tolerances. A further approach to reduce the geometric deviations due to robot deformation is reducing the forming forces in robot-based two-point incremental forming. This is achieved by a modular vibration unit that has been specially developed for this purpose. The introduction of ultrasonic vibrations into the forming process has been shown to reduce the forces in the sheet metal plane by 70%. As a result, the sensor network and the introduction of ultrasonic vibrations provide a robust foundation for the advancement of higher accuracy classes with cost-effective robot technology, which is becoming increasingly crucial in the industry.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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