High efficiency and high automation are essential in the process of metal cutting. How to control the chip will affect processing quality, cutting tool life and productivity greatly. With the development of image processing technology, machine vision has been widely used in real-time monitoring of chip shape. A set of machine vision detection system is developed for realizing image capture, image processing, image pattern matching and image analysis in real time in this paper. Especially, dynamic template is designed to match the complex chip. In this system, LabVIEW is used as system platform, QP 300 picture capture card of Daheng-Image cooperation is used as image capture hardware, LED of CCS cooperation is used as light source. The actual operation shows that this system can identify typical C shape chip and spiral shape chip. Meanwhile, other functions are developed, such as parameter optimization and network transmission.
Along with the fast development of image technology, its application has nearly reached every field. Image measurement technology has larger measurement speed and its results are prone to observe, contrast, analyze and save. In this study, an image measurement system composed of a CCD camera, a computer and a LED lamp-house, was used to study the characteristic of electron images of machined surfaces obtained under different processing methods. The corresponding relations between the character of different surface textures and of different electron images were established. The character of the machined surfaces' images with different cutting parameters was also studied and the image character parameters' range of standard roughness was established. Meanwhile, image measurement methods of the machined surfaces' quality were studied. Image methods and evaluation indicator in this study have good application performance, which were established by comparing them with traditional measurement methods' results.