An intelligent fuzzy c-means system for process monitoring and recognition of process disturbances during short- circuiting gas metal arc welding （GMAW） is introduced in this paper. The raw measured and statisticall...An intelligent fuzzy c-means system for process monitoring and recognition of process disturbances during short- circuiting gas metal arc welding （GMAW） is introduced in this paper. The raw measured and statistically test data of probability density distribution （ PDD ） and class frequency distribution （ CFD ） of welding electrical parameters are further processed into a 7-dimensional array which is designed to describe various welding conditions, and is employed as input vector of the intelligent fuzzy c-means system. The fuzzy c-means system is used to conduct process monitoring and automatic recognition. The correct recognition rate of 24 test data under 8 kinds of welding condition is 92%.展开更多
基金The authors are grateful to the financial support provided by the National Natural Science Foundation of China under grant No. 51005106, Research Fund for the Doctoral Program of Jiangsu Uni- versity of Science and Technology under grant No. 35060902, A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘An intelligent fuzzy c-means system for process monitoring and recognition of process disturbances during short- circuiting gas metal arc welding （GMAW） is introduced in this paper. The raw measured and statistically test data of probability density distribution （ PDD ） and class frequency distribution （ CFD ） of welding electrical parameters are further processed into a 7-dimensional array which is designed to describe various welding conditions, and is employed as input vector of the intelligent fuzzy c-means system. The fuzzy c-means system is used to conduct process monitoring and automatic recognition. The correct recognition rate of 24 test data under 8 kinds of welding condition is 92%.
