Research On Design And Test Method Of Motion Control Platform With Integration Of Machine Vision

Motion control technology is one of the core technologies to promote manufacturing innovation. In the process of industrial development, functional requirements of the motion control system are diverse, so an open and flexible architecture is needed, and software-oriented method is necessary for realizing this architecture. With the help of motion control bus, motion controller,servo systems, and other terminal modules are formed to be a digitized whole., Also, the mature of real-time Ethernet technology greatly contributed to the development of motion control technology, also promote the implementation of software-oriented architecture as well. In order to design quality and reliable, motion control system with rich functions rapidly, the architecture of the control system should be open and reconfigurable. Also a convenient and effective testing method is needed in order to test functions of constructed motion control system.Machine vision system is typically used as a key function expansion of the motion control system. For PC-based machine vision systems, powerful computing performance can effectively shorten the image processing time. But because Windows is not a real-time operating system, the time jitter of image acquisition, and, processing and interaction between machine vision and motion control, is large. It cannot be applied to the applications which demand real-time performance. Embedded systems dedicated to image acquisition and processing have good real-time performance and can transmit the image processing results to motion controller via communication bus or I/O. But developers can only use the built-in functions due to lack of expansion abilityTherefore, a kind of open real-time machine vision system is needed for the motion control system. The design method of motion control platform with integration of machine vision is studied. In this platform, machine vision and motion control function are placed in a common real-time domain. With this design, the real-time performance of machine vision is can be improved effictively.The basic real-time runtime is designed in open soft motion controller based on Windows+ Kithara Real-time Suite (KRTS). After testing, the maximum value of system response time to network card can be less than 13μs. Ethernet for Manufacture Automation Control (EtherMAC) master protocal stack is developed. With this protocal stack, the communication cycle can be less than 100μs. The developing method of an open soft motion controller is given, and its programmable interface is designed under the motion control specification of PLCopen. Control resource layer is designed to reduce the coupling between real-time Ethernet and soft motion controller. Machine vision running in real-time domain uses open image transfer protocol GigE Vision as acquisition interface and can reuse the rich image processing software resource on Windows. The feasibility of motion control platform with integration of machine vision is verified through designing of a visually guided robot control system.Motion control bus builds seamless data connection between components in motion control system, which is also the direct interface of software function expression. Based on the motion control bus transfer data, a software function test method of motion control system based on data reverse analysis is proposed according to real-time Ethernet communication. A kind of data monitoring method without delay based on Field Programmable Gate Array (FPGA) is developed to avoid disturbing the communicating of Ethernet. The parse mechanism of data link layer and application layer for EtherMAC is developed, so that motion control data can be extracted.This mechanism is verified with an EtherMAC based CNC system. With this mechanism, the software function of motion control system can be evaluated wihout modification of mechanical and electrical connections.These research results provide an open and low cost implementation scheme for real-time machine vision applications, and provide a simple method for testing the function of the system.