Design Of Remote Workpiece Detection System Based On Embedded Technology

With the rapid development of economic, the production scale is expanding quickly. The manufacture quality demand of workpiece is required higher and higher, which puts forward new requirements for the workpiece detection technology. Due to its low efficiency、intensive labour、high cost and low precision, the traditional artificial measurement has been already difficult to meet demands of actual production. It may lead to the increase of reject rate. In order to reduce staff labour intensity、enhance production efficiency and increase the staff’s enthusiasm for work as much as possible, it is important to design a type of workpiece dimensional detection system.The paper has designed a new type of remote workpiece detection system based on embedded technology, which integrates using various technology such as embedded technology、image compression technology、network technology and machine vision technology. Designed the embedded system’s web server with high performance and low cost that have the processor STM32F407based on Cortex-M4core as core. The system combined the unique DCMI、SDIO、FSMC interface and MAC module consists of many peripherals, such as CMOS image sensor PHY、SDcard、SRAM and Flash storage circuit, which can realize image supervisory and image processing functions on the unattended environment.Due to digital image with huge amount of data brings a great of difficulty to the transport and storage, the workpiece detection system adopts JPEG digital video compressing. The workpiece detection system runs real-time operating system FreeRTOS, which can allocate hardware and software resources properly and achieve real-time multitask scheduling and management. The LwIP protocol stack that light weight embedded TCP/IP protocol stack with the support of FreeRTOS achieves network communication between embedded web server and client.This detection system testing environment is what joins embedded web server and computers together within one local area network (LAN) through network switch. The client communicates with embedded web server through browsers. The web pages of client is constructed by HTML language、JavaScript technology and Canvas technology. The compressed image can be obtained on the web pages of client clearly and fluently, the running state of workpiece can be monitored by the compressed image. The web pages will switch into image processing mode when the workpiece enter into the detection station. The image is transformed over gray transform、median filtering、the segmentation algorithm of the optimal threshold and Robert edge detection to remove the impurities of the image and get the edge information. At the moment, the profile of workpiece can be seen in the image. Finally, according to the principle of JavaScript event listener, the pixel distance of the workpiece in the image is obtained. With the proportion of pixel distance and the actual distance, the actual length of the workpiece can be displayed to verify the application value of the system.