Journal of the Korean Society of Manufacturing Process Engineers (한국기계가공학회지)
- Volume 4 Issue 3
- /
- Pages.57-62
- /
- 2005
- /
- 1598-6721(pISSN)
- /
- 2288-0771(eISSN)
A Study on Fault Diagnosis in Face-Milling using Artificial Neural Network
인공신경망을 이용한 정면밀링에서 이상진단에 관한 연구
- Kim, Won-Il ;
- Lee, Yun-Kyung ;
-
Wang, Dyuk-Hyun
;
-
Kang, Jae-Kwan
;
- Kim, Byung-Chang ;
- Lee, Kwan-Cheol ;
- Jung, In-Ryung
- 김원일 (경남대학교 기계자동화 공학부) ;
- 이윤경 (경남대학교 기계자동화 공학부) ;
-
왕덕현
(경남대학교 기계자동화 공학부)
;
-
강재관
(경남대학교 기계자동화 공학부)
;
- 김병창 (경남대학교 기계자동화 공학부) ;
- 이관철 (경남대학교 대학원 기계공학과) ;
- 정인룡 (경남대학교 대학원 기계공학과)
- Published : 2005.09.30
Abstract
Neural networks, which have learning and self-organizing abilities, can be advantageously used in the pattern recognition. Neural network techniques have been widely used in monitoring and diagnosis, and compare favourable with traditional statistical pattern recognition algorithms, heuristic rule-based approaches, and fuzzy logic approaches. In this study the fault diagnosis of the face-milling using the artificial neural network was investigated. After training, the sample which measure load current was monitored by constant output results.
Keywords