The role of industrial lenses in machine vision
The role of machine vision in controlling industrial processes is becoming more and more important, especially in the fields of robot guidance, target recognition and quality assurance. The current vision system has gone beyond those basic functions (such as identifying parts and determining directions), and can also provide information about subsequent functions, such as moving objects from one location to another. For assembly lines and robotic systems used in a large number of inspection operations, such as automobile production and inspection lines, conveyor belts are generally a reference. Here, the robot performs two tasks: recognition and transmission. In most machine vision applications, optical control is very important. Robot vision systems also require extremely high repeatability, so it is necessary to reduce jitter to provide clear images. On a large-scale unit inspection line like a pharmaceutical factory, the vision system must be able to identify defective packages, unreadable labels, and missing products. The vision system must be able to quickly identify and measure square, round and elliptical objects with extremely high accuracy. Improving the accuracy of the machine vision system can help maintain a uniform packaging surface and color. For food inspection systems, the size, color, density and shape of the product need to rely on multiple inspections to confirm. Multivariate machine vision systems can be both color cameras and black and white cameras, and generally use structured lighting methods to establish the appearance and internal structure of the product. Even if the camera, analysis software and lighting are very important to the machine vision system, the key component may still be imaging [industrial lens]. For the system to fully utilize its functions, the lens must meet the requirements. When choosing a lens for a control system, machine vision integrators should consider four main factors: 1. Can detect object categories and characteristics; 2. Depth of field or focal length; 3. Loading and detection distance; 4. Operating environment. The ability of an industrial lens to identify line coupling or dot pitch of a specific width under specified light conditions determines its resolution. The resolution is generally displayed as an image by the module conversion function (MTF). The graph shows the relative contrast that is feasible at a specified line coupling frequency. Distortion, chromatic aberration, and other wavefront distortions all affect the slope of the curve, causing the curve to deviate from the ideal state or the optical performance of the diffraction limit. The lens scheme sometimes lists the object resolution in units of line couplings per millimeter (lp/mm), and then divide this value by 1000 to predict the object resolution per micrometer of the lens. When performing surface analysis, generally not only a camera and industrial lens are used, but it is also valuable to understand the inherent deviation of the lens. Bias refers to the optical errors in the lens, which can cause image quality differences at different points in the same picture. The analysis generally includes the laser line and the light in other images, which can ensure the accuracy of the measurement. Some software programs can eliminate errors such as distortion caused by the lens, so only the profiling data is obvious in the image.