The development process of an industrial machine vision system mainly includes the following stages:
Requirements analysis and system design: cooperate with users to clarify the functional and performance requirements of the system, and design the overall architecture of the system.
Software and hardware selection: According to the requirements analysis results, select suitable software and hardware equipment, including optical sensors, cameras, light sources, image acquisition equipment, processors, etc.
Software development: According to the system design, write machine vision software, including image processing algorithms, image analysis and recognition algorithms, etc. Programming languages such as C++, Python, etc., and machine vision libraries such as OpenCV, Halcon, etc. can be used.
Test and Verification: Test the software and hardware in the laboratory environment to verify whether the functions and performance of the system meet the requirements. Including testing image quality, algorithm accuracy, and real-time performance.
System integration acceptance: integrate software and hardware, and conduct overall system testing and verification. Ensure that the various components work together to achieve the expected functionality and performance.
Trial operation and tuning: Conduct a trial run in the actual production environment, collect feedback and perform system tuning to ensure that the system runs stably and meets actual needs.
The above is a simplified industrial machine vision system development process. The actual development may involve more details and complexity, which needs to be adjusted and supplemented according to the needs and requirements of specific projects.