In machine vision systems, light sources are often used to improve the effectiveness of imaging, which has improved the efficiency and accuracy of detection. So different materials and features often require different light sources to have significant effects, so let's take a look at how to choose the right wavelength of light source today.
First, let's look at light and wavelength. Light is an electromagnetic wave that travels in the form of waves. As shown in the figure below, the length of a full wave period of a light wave during propagation, i.e., the distance from one peak (or trough) to an adjacent peak (or trough), is the wavelength. It is usually expressed in nanometers (nm).
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Second, the classification of wavelengths.
Light is reflected, refracted, transmitted, and absorbed when acting on an object. The machine vision industry makes the most common use of reflected light. Therefore, when selecting a light source, it is necessary to select the appropriate wavelength and mode of action according to the material, color, and characteristics of the object. 380nm to 760nm is visible light, between which is composed of seven colors: violet, blue, cyan, green, yellow, orange and red, white light is composed of light mixtures of different wavelengths in visible light, and between 10nm and 380nm is ultraviolet ray, and between 760nm and 1000um is infrared.
The color of visible light is directly related to wavelength. Among the three primary colors of red, green and blue, red light has the longest wavelength, followed by green light, and blue light has the shortest wavelength. White light is composed of a mixture of red, green, and blue light. The object is prone to reflecting light of the same wavelength or similar wavelength. If the object is red, it is easy to reflect red light. If the object is white, all three types of light are easily reflected. If the object is black, all three types of light will be absorbed. Therefore, when the object to be observed has a color, it is necessary to select the correct wavelength of light according to the above theory to obtain a more obvious contrast between light and dark**.
In addition, infrared wavelength light has strong light penetration, which can be used for applications that need to observe the next layer of material through one layer of matter, and blue light has a short wavelength and weak penetration, so if you need to detect defects such as scratches on the plane, the blue light effect will be more prominent.
Third, the reflectivity of different metal materials to different light sources is also different. There are some special bands that are not uncommon in machine vision applications. For example, short-wave infrared and near-infrared are often used for silicon crystal detection, solar cell inspection, agricultural products and food classification, etc.; Ultraviolet light is often used for glue curing, photoluminescence detection, etc. In practical machine vision applications, we can select the light source of the corresponding wavelength band according to the material characteristics of the object to be measured, or we can use the filter to filter out the unwanted wavelength, and only allow the light of a certain wavelength band to enter the lens for imaging, so as to improve the image quality.
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