Machine Vision Applications In Online Detection Of Defects On High-speed Bar Copper

In copper bars Industrial production, various reasons make copper strips surfacehave defects, usually the factory use manual inspection method, it is inefficient and notvery high accuracy. Response to these questions, we studied the existing machinevision technologies, and gave a applications in online detection of defects onhigh-speed bar copper, the device is better on the complex environment, also istimeliness, accuracy and so on.This application in online detection of defects on high-speed bar copper includeslighting systems, industrial cameras, industrial computer, image processing softwareand other components. Lighting system uses coaxial illumination technology to gethigher quality copper strips images, then transfer the collected images to IPC and doreal-time processing, output results, record and save defects at last. This device usedLabVIEW and NI’s Machine Vision modules to program, the algorithm process is:firstly, image preprocessing, using Gaussian filter for image denoising, using theclosing operation of mathematical morphology to remove small defects that do notbelong to defects, and then using the maximum between-class variance thresholdingthe image, then in edge detection, using Sobel operator to select the edge of copperstrips and defects in the images, Setting range test line to identify the defects based onthe form of copper strips, showing Pass/Fail according to presence or absence ofdefects, and displaying, recording and saving the system time when defects appear andthe distance to the beginning. A large amount of experimental results implied that thedevice is high accuracy, real time, automatization.