Automatic vision inspection technology shows a high potential for quality inspection,\nand has drawn great interest in micro-armature manufacturing. Given that the inspection process is\nhighly influenced by the lack of real standardization and efficiency performed with the human eye,\nthus, it is necessary to develop an automatic defect detection process. In this work, an elaborated\nvision system for the defect inspection of micro-armatures used in smartphones was developed.\nIt consists of two parts, the front-end module and the deep convolution neural networks (DCNNs)\nmodule, which are responsible for different areas. The front-end module runs first and the DCNNs\nmodule will not run if the output of the front-end module is negative. To verify the application of\nthis system, an apparatus consisting of an objective table, control panel, and a camera connected to\na Personal Computer (PC) was used to simulate an industrial position of production. The results\nindicate that the developed vision system is capable of defect detection of micro-armatures.
Loading....