The Research On Threshing For Aggregate From A Gravity Flow

In the procedure of making the aggregate for industry and enterprise, it needs to do non-stop online examine and auto-control urgently. So, this paper puts the key point to study the problem of thresholding algorithms about fallen aggregate images. Meanwhile, this paper puts forward the method of collecting, handling and analyzing aggregate images in real time, using the computer-image-examine skill. In this way, the traditional handicraft would be replaced. And the labor intensity would be reduced to a great extent. As a result, it will improve the efficiency of examining and analyzing.At first, this paper makes an explanation of the significance and content of the exact study task, as well as the process of collection and analysis of aggregates. And then, it tells us some relevant things, such as the components of vision system, the fundamental knowledge related to pre-treating images, the composition of digital image handling system, the tool for dealing with images-histogram, the methods of pre-treating and cutting apart images, and its relative course. The real-time aggregate images are collected by the CCD camera that is equipped on the conveyer belt. After conveyed quickly and displayed through vision system, thecollected images deal with image filtering and sharpening (strengthen) pretreatment, and shifting images. After that, they become more authentic and distinct, and provide an appropriate condition for the study of aggregate images segmentation. It can be concluded from the analysis that there are two circumstances about the aggregate image thresholding algorithms. On the first circumstance, there is no difference between background and surrounding, and the aggregate image thresholding algorithms is suitable to adopt OPT and BCV. On the second circumstance, the backgrounds don't agree with each other, or its brightness and darkness changes along with time. According to this case, there is a new thresholding algorithms-BCV for fallen aggregate images. Through the study on aggregate thresholding algorithms, we can control the sizes and shapes of fallen aggregates properly. Just in this way the aggregate manufacturers can find out their quality problems in time and eliminate quality defects. It also supplies a strong and scientific guarantee to improve quality and productivity.